[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"seo-content-skill-vector-databases-global":3,"job-search-\u002Fde\u002Fjobs-by-skill\u002Fvector-databases?page=2":4,"skill-page-filters-\u002Fde\u002Fjobs-by-skill\u002Fvector-databases?page=2":797,"featured-jobs-\u002Fde\u002Fjobs-by-skill\u002Fvector-databases?page=2":1011},{},{"total":5,"jobs":6},91,[7,67,113,158,201,242,258,327,376,408,451,485,526,566,594,616,660,691,715,747],{"id":8,"slug":9,"title":10,"raw_title":11,"is_featured":12,"company":13,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":16,"processed_country_iso_code_gmaps":18,"processed_home_office":20,"processed_salary_min":21,"processed_salary_max":22,"processed_salary_currency":23,"processed_salary_source":24,"processed_working_hours":25,"processed_employment_types":27,"processed_it_skills":28,"processed_it_skills_labels":31,"processed_job_expertise_skills":50,"processed_job_expertise_skills_labels":51,"max_cpc":66,"actual_cpc":66},83669,"staff-engineer-applied-ai-government-employees-insurance-company","Staff Engineer - Applied AI",null,false,{"name":14,"slug":15,"logo_url":11},"Government Employees Insurance Company","government-employees-insurance-company",[17],"Bethesda",[19],"US","hybrid",115000,230000,"USD","estimated",[26],"FULL_TIME","permanent",{"java":29,"python":30,"embabel":29,"langchain":30,"langgraph":30,"langsmith":30,"spring ai":29,"llamaindex":30,"langchain4j":29,"openai apis":30,"hugging face":30,"anthropic apis":30,"service design":30,"knowledge graphs":30,"vector databases":30,"distributed systems":30,"reliability engineering":30,"performance optimization":30},3,4,[32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49],"Python","LangChain","LangGraph","LangSmith","LlamaIndex","Hugging Face","OpenAI APIs","Anthropic APIs","Vector Databases","Knowledge Graphs","Distributed Systems","Service Design","Performance Optimization","Reliability Engineering","Java","Spring AI","LangChain4j","Embabel",{"ai safety":29,"ai governance":29,"ai monitoring":29,"generative ai":30,"fraud modeling":29,"ontology design":29,"anomaly modeling":29,"agentic workflows":30,"llm-based systems":30,"document intelligence":29,"regulatory compliance":29,"intelligent automation":30,"applied machine learning":30,"retrieval-augmented generation":30},[52,53,54,55,56,57,58,59,60,61,62,63,64,65],"Applied Machine Learning","Generative AI","LLM-based Systems","Agentic Workflows","Intelligent Automation","Retrieval-Augmented Generation","AI Safety","AI Governance","AI Monitoring","Regulatory Compliance","Document Intelligence","Fraud Modeling","Anomaly Modeling","Ontology Design",1,{"id":68,"slug":69,"title":70,"raw_title":11,"is_featured":12,"company":71,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":75,"processed_country_iso_code_gmaps":77,"processed_home_office":20,"processed_salary_min":79,"processed_salary_max":80,"processed_salary_currency":81,"processed_salary_source":24,"processed_working_hours":82,"processed_employment_types":27,"processed_it_skills":83,"processed_it_skills_labels":84,"processed_job_expertise_skills":96,"processed_job_expertise_skills_labels":97,"max_cpc":66,"actual_cpc":66},81678,"ai-transformation-lead-mfd3314-allianz-insurance","AI Transformation Lead (m\u002Ff\u002Fd)_3314",{"name":72,"slug":73,"logo_url":74},"Allianz Insurance","allianz-insurance","https:\u002F\u002Fcdn.phenompeople.com\u002FCareerConnectResources\u002FAISAIPGB\u002Fimages\u002FHeader-1706868786965.svg",[76],"BARCELONA",[78],"ES",70000,100000,"EUR",[26],{"aws":29,"gcp":29,"rag":30,"apis":29,"llms":30,"azure":29,"ci\u002Fcd":29,"genai":30,"mlops":30,"modelops":30,"machine learning":29,"vector databases":29},[85,86,87,88,89,90,91,92,40,93,94,95],"GenAI","LLMs","RAG","MLOps","ModelOps","Azure","AWS","GCP","APIs","CI\u002FCD","Machine Learning",{"nist":29,"eu ai act":29,"ai governance":30,"iso\u002Fiec 27001":29,"responsible ai":30,"sla management":30,"cost management":30,"privacy controls":30,"adoption programs":30,"security controls":30,"vendor management":30,"kpi\u002Fokr definition":30,"ai\u002Fml transformation":30,"regulatory compliance":30,"digital transformation":30,"training and enablement":30,"business case development":30},[98,99,59,100,101,102,61,103,104,105,106,107,108,109,110,111,112],"AI\u002FML Transformation","Digital Transformation","Responsible AI","Security Controls","Privacy Controls","ISO\u002FIEC 27001","NIST","EU AI Act","Vendor Management","SLA Management","Cost Management","KPI\u002FOKR Definition","Business Case Development","Adoption Programs","Training and Enablement",{"id":114,"slug":115,"title":116,"raw_title":11,"is_featured":12,"company":117,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":120,"processed_country_iso_code_gmaps":121,"processed_home_office":123,"processed_salary_min":124,"processed_salary_max":125,"processed_salary_currency":126,"processed_salary_source":24,"processed_working_hours":127,"processed_employment_types":27,"processed_it_skills":128,"processed_it_skills_labels":129,"processed_job_expertise_skills":140,"processed_job_expertise_skills_labels":141,"max_cpc":66,"actual_cpc":66},86455,"manager-advanced-analytics-prudential-hong-kong-limited","Manager, Advanced Analytics",{"name":118,"slug":119,"logo_url":11},"Prudential Hong Kong Limited","prudential-hong-kong-limited",[],[122],"HK","onsite",800000,1200000,"HKD",[26],{"aws":29,"gcp":29,"sql":30,"azure":29,"ci\u002Fcd":29,"mlops":30,"python":30,"pytorch":30,"xgboost":30,"lightgbm":30,"ai agents":29,"tensorflow":30,"scikit-learn":30,"generative ai":29,"version control":29,"vector databases":29,"large language models (llms)":29,"retrieval-augmented generation (rag)":29},[32,130,131,132,133,134,135,90,91,92,88,94,136,53,137,138,40,139],"Scikit-learn","XGBoost","LightGBM","TensorFlow","PyTorch","SQL","Version Control","Large Language Models (LLMs)","Retrieval-Augmented Generation (RAG)","AI Agents",{"churn prediction":30,"machine learning":30,"model deployment":30,"model evaluation":30,"model monitoring":30,"data manipulation":30,"propensity models":30,"forecasting models":30,"feature engineering":30,"predictive modeling":30,"model explainability":30,"statistical analysis":30,"recommendation engines":30,"optimization techniques":30,"hyperparameter optimization":30,"production model management":30,"customer lifetime value modeling":30},[95,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157],"Predictive Modeling","Statistical Analysis","Optimization Techniques","Feature Engineering","Model Evaluation","Hyperparameter Optimization","Model Explainability","Data Manipulation","Model Deployment","Model Monitoring","Production Model Management","Customer Lifetime Value Modeling","Churn Prediction","Recommendation Engines","Forecasting Models","Propensity Models",{"id":159,"slug":160,"title":161,"raw_title":11,"is_featured":12,"company":162,"raw_hiringOrganization_logo_url":166,"processed_city_gmaps":167,"processed_country_iso_code_gmaps":169,"processed_home_office":20,"processed_salary_min":171,"processed_salary_max":172,"processed_salary_currency":81,"processed_salary_source":24,"processed_working_hours":173,"processed_employment_types":27,"processed_it_skills":174,"processed_it_skills_labels":175,"processed_job_expertise_skills":187,"processed_job_expertise_skills_labels":188,"max_cpc":66,"actual_cpc":66},87969,"ki-engineer-mwd-im-bereich-technologie-und-prozesse-it-sparkassen-versicherung-sachsen","KI-Engineer (m\u002Fw\u002Fd) im Bereich Technologie und Prozesse (IT)",{"name":163,"slug":164,"logo_url":165},"Sparkassen-Versicherung Sachsen","sparkassen-versicherung-sachsen","\u002Fimages\u002Flogos\u002Fsparkassen-versicherung-sachsen-allgemeine-versicherung-aktiengesellschaft-logo.png","https:\u002F\u002Finstitute-logos.sparkasse.de\u002F90090119.svg",[168],"Dresden",[170],"DE",60000,80000,[26],{"c++":29,"git":29,"apis":30,"java":29,"llms":29,"mcps":29,"ci\u002Fcd":29,"mlops":29,"docker":29,"python":30,"skills":29,"azure ai":29,"transformers":29,"microservices":29,"data processing":29,"knowledge graphs":29,"vector databases":29,"rag architectures":29,"cloud architectures":29},[32,176,46,40,177,93,178,179,180,94,181,182,88,41,183,86,184,185,186],"C++","Data Processing","Microservices","Azure AI","Cloud Architectures","Git","Docker","Transformers","RAG Architectures","MCPs","Skills",{"monitoring":29,"data science":30,"data protection":29,"machine learning":30,"knowledge transfer":29,"model optimization":29,"ai system operation":30,"information security":29,"software development":30,"regulatory compliance":29,"technology evaluation":29,"continuous improvement":29,"steering external partners":29,"technical architecture design":30},[189,95,190,191,192,193,194,195,196,61,197,198,199,200],"Software Development","Data Science","AI System Operation","Technical Architecture Design","Technology Evaluation","Model Optimization","Information Security","Data Protection","Monitoring","Continuous Improvement","Steering External Partners","Knowledge Transfer",{"id":202,"slug":203,"title":204,"raw_title":11,"is_featured":12,"company":205,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":208,"processed_country_iso_code_gmaps":210,"processed_home_office":20,"processed_salary_min":212,"processed_salary_max":213,"processed_salary_currency":214,"processed_salary_source":24,"processed_working_hours":215,"processed_employment_types":27,"processed_it_skills":216,"processed_it_skills_labels":217,"processed_job_expertise_skills":230,"processed_job_expertise_skills_labels":231,"max_cpc":66,"actual_cpc":66},83095,"gcp-data-ai-engineer-as-f337-deutsche-india-private-limited-pune-branch-2","GCP Data & AI Engineer, AS",{"name":206,"slug":207,"logo_url":11},"F337 Deutsche India Private Limited, Pune Branch","f337-deutsche-india-private-limited-pune-branch",[209],"Pune",[211],"IN",3000000,5000000,"INR",[26],{"aws":29,"gcp":30,"sql":30,"llms":30,"azure":29,"ci\u002Fcd":30,"docker":30,"python":30,"bigquery":30,"cloud run":30,"rest apis":30,"terraform":30,"cloud build":30,"dialogflow cx":30,"apache airflow":30,"cloud composer":30,"embedding models":30,"vector databases":30,"artifact registry":30,"gemini enterprise agent platform":30,"google agent development kit (adk)":30},[32,135,92,218,219,220,221,222,94,223,224,182,225,226,227,228,40,229,86,90,91],"BigQuery","Cloud Composer","Apache Airflow","Cloud Run","Terraform","Cloud Build","Artifact Registry","REST APIs","Dialogflow CX","Gemini Enterprise Agent Platform","Google Agent Development Kit (ADK)","Embedding Models",{"agentops":30,"system design":30,"data engineering":30,"conversational ai":30,"production support":30,"generative ai systems":30,"infrastructure as code":30,"security and governance":30,"ai application development":30,"agentic ai application development":30},[232,233,234,235,236,237,238,239,240,241],"Data Engineering","AI Application Development","System Design","Conversational AI","Generative AI Systems","Agentic AI Application Development","AgentOps","Infrastructure as Code","Security and Governance","Production Support",{"id":243,"slug":244,"title":204,"raw_title":11,"is_featured":12,"company":245,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":246,"processed_country_iso_code_gmaps":247,"processed_home_office":20,"processed_salary_min":212,"processed_salary_max":213,"processed_salary_currency":214,"processed_salary_source":24,"processed_working_hours":248,"processed_employment_types":27,"processed_it_skills":249,"processed_it_skills_labels":251,"processed_job_expertise_skills":252,"processed_job_expertise_skills_labels":253,"max_cpc":66,"actual_cpc":66},83093,"gcp-data-ai-engineer-as-f337-deutsche-india-private-limited-pune-branch",{"name":206,"slug":207,"logo_url":11},[209],[211],[26],{"aws":250,"gcp":30,"sql":30,"llms":30,"azure":250,"ci\u002Fcd":30,"docker":30,"python":30,"bigquery":30,"cloud run":30,"rest apis":30,"terraform":30,"cloud build":30,"dialogflow cx":30,"apache airflow":30,"cloud composer":30,"embedding models":30,"vector databases":30,"artifact registry":30,"gemini enterprise agent platform":30,"google agent development kit (adk)":30},2,[32,135,92,218,219,220,221,222,94,223,224,182,225,226,227,228,40,229,86,90,91],{"etl testing":30,"rag systems":30,"generative ai":30,"system design":30,"data engineering":30,"agentic workflows":30,"conversational ai":30,"production support":30,"ml model deployment":30,"infrastructure as code":30,"security and governance":30,"data pipeline development":30,"ai application development":30},[232,233,234,53,254,55,235,255,256,257,239,240,241],"RAG Systems","ML Model Deployment","Data Pipeline Development","ETL Testing",{"id":259,"slug":260,"title":261,"raw_title":11,"is_featured":12,"company":262,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":263,"processed_country_iso_code_gmaps":264,"processed_home_office":20,"processed_salary_min":265,"processed_salary_max":266,"processed_salary_currency":214,"processed_salary_source":24,"processed_working_hours":267,"processed_employment_types":27,"processed_it_skills":268,"processed_it_skills_labels":269,"processed_job_expertise_skills":304,"processed_job_expertise_skills_labels":305,"max_cpc":66,"actual_cpc":66},83099,"gcp-full-stack-data-ai-engineer-as-f337-deutsche-india-private-limited-pune-branch","GCP Full-Stack Data & AI Engineer, AS",{"name":206,"slug":207,"logo_url":11},[209],[211],2000000,3500000,[26],{"git":30,"iam":30,"jwt":30,"sql":30,"cors":30,"ci\u002Fcd":30,"flask":30,"owasp":30,"react":30,"docker":30,"pytest":30,"python":30,"angular":30,"fastapi":30,"postman":30,"pub\u002Fsub":29,"bigquery":30,"cloud run":30,"cloud sql":29,"firestore":29,"oauth 2.0":30,"rest apis":30,"terraform":30,"embeddings":30,"guardrails":29,"javascript":30,"typescript":30,"cloud build":30,"memorystore":29,"api gateways":30,"cloud storage":30,"dialogflow cx":30,"gemini models":30,"rate limiting":30,"apache airflow":29,"cloud composer":29,"openid connect":30,"secret manager":30,"cx agent studio":30,"human oversight":29,"input validation":30,"vector databases":30,"artifact registry":30,"secrets management":30,"google cloud platform":30,"google cloud operations":30,"agent-to-agent protocols":29,"multi-agent orchestration":29,"google agent development kit (adk)":30},[32,135,270,271,272,273,274,275,225,276,221,218,277,278,219,220,279,280,281,282,181,182,222,224,223,94,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,226,299,228,300,301,302,303],"JavaScript","TypeScript","React","Angular","FastAPI","Flask","Google Cloud Platform","Cloud Storage","Secret Manager","Pub\u002FSub","Cloud SQL","Firestore","Memorystore","OAuth 2.0","OpenID Connect","JWT","IAM","API gateways","CORS","rate limiting","secrets management","input validation","OWASP","Postman","Pytest","Google Cloud Operations","Gemini models","embeddings","vector databases","CX Agent Studio","multi-agent orchestration","agent-to-agent protocols","guardrails","human oversight",{"devops":30,"agentic ai":30,"data lineage":30,"data quality":30,"generative ai":30,"orchestration":30,"ai engineering":30,"data modelling":30,"responsible ai":30,"data governance":30,"data engineering":30,"capacity planning":30,"incident response":30,"secure publishing":30,"cloud architecture":30,"query optimization":30,"architecture design":30,"quality engineering":30,"security engineering":30,"software engineering":30,"full-stack development":30,"technical documentation":30,"operations & reliability":30,"batch and streaming design":30},[306,307,232,308,309,310,311,312,313,53,314,315,316,317,318,319,320,321,322,323,324,325,326,100],"Software Engineering","Full-Stack Development","AI Engineering","Cloud Architecture","DevOps","Quality Engineering","Security Engineering","Operations & Reliability","Agentic AI","Technical Documentation","Architecture Design","Incident Response","Capacity Planning","Data Modelling","Batch and Streaming Design","Orchestration","Data Quality","Data Lineage","Data Governance","Query Optimization","Secure Publishing",{"id":328,"slug":329,"title":330,"raw_title":11,"is_featured":12,"company":331,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":334,"processed_country_iso_code_gmaps":336,"processed_home_office":20,"processed_salary_min":337,"processed_salary_max":338,"processed_salary_currency":23,"processed_salary_source":24,"processed_working_hours":339,"processed_employment_types":27,"processed_it_skills":340,"processed_it_skills_labels":341,"processed_job_expertise_skills":358,"processed_job_expertise_skills_labels":359,"max_cpc":66,"actual_cpc":66},88143,"director-data-and-analytics-ai-engineering-hartford-fire-ins-co","Director Data and Analytics AI Engineering",{"name":332,"slug":333,"logo_url":11},"Hartford Fire Ins. Co","hartford-fire-ins-co",[335],"Hartford",[19],156000,234000,[26],{"llms":30,"devops":29,"pinecone":29,"postgres":29,"data apis":29,"snowflake":30,"vertex ai":29,"data lakes":30,"opensearch":29,"ai platforms":30,"data pipelines":30,"data integration":30,"data warehousing":30,"vector databases":30,"agentic frameworks":29,"cloud technologies":30,"prompt engineering":30,"business intelligence":30,"real-time data streaming":29,"retrieval-augmented generation (rag)":30},[342,343,86,344,138,40,345,346,347,348,349,350,351,352,353,354,310,355,356,357],"Snowflake","AI Platforms","Prompt Engineering","Vertex AI","Postgres","OpenSearch","Pinecone","Data Pipelines","Data Warehousing","Data Lakes","Data Integration","Business Intelligence","Cloud Technologies","Data APIs","Real-time Data Streaming","Agentic Frameworks",{"ai\u002Fml":30,"pricing":30,"reserving":30,"data quality":30,"underwriting":30,"data modeling":30,"data products":30,"agile at scale":30,"data governance":30,"semantic layers":30,"data engineering":30,"budget management":30,"data architecture":30,"data modernization":30,"actuarial analytics":30,"financial analytics":30,"insurance analytics":30,"portfolio management":30,"analytics solution delivery":30},[232,360,324,322,361,362,363,364,365,366,367,368,369,370,371,372,373,374,375],"Data Architecture","Actuarial Analytics","Insurance Analytics","Pricing","Reserving","Underwriting","Portfolio Management","Financial Analytics","Budget Management","Agile at Scale","AI\u002FML","Data Modeling","Data Modernization","Semantic Layers","Data Products","Analytics Solution Delivery",{"id":377,"slug":378,"title":379,"raw_title":11,"is_featured":12,"company":380,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":383,"processed_country_iso_code_gmaps":385,"processed_home_office":20,"processed_salary_min":171,"processed_salary_max":387,"processed_salary_currency":81,"processed_salary_source":24,"processed_working_hours":388,"processed_employment_types":27,"processed_it_skills":389,"processed_it_skills_labels":390,"processed_job_expertise_skills":400,"processed_job_expertise_skills_labels":401,"max_cpc":66,"actual_cpc":66},84254,"senior-aillm-data-scientist-in-agentic-ai-ing-hubs-bv-turkiye-2","Senior AI\u002FLLM Data Scientist in Agentic AI",{"name":381,"slug":382,"logo_url":11},"ING Hubs B.V. Turkiye","ing-hubs-bv-turkiye",[384],"Sarıyer",[386],"TR",90000,[26],{"peft":29,"crewai":29,"python":30,"autogen":29,"azure ai":29,"langchain":29,"langgraph":29,"vertex ai":29,"embeddings":30,"fine-tuning":29,"openai apis":29,"api integration":30,"semantic kernel":29,"vector databases":30,"prompt engineering":30,"workflow orchestration":29,"distributed ai architectures":29,"retrieval-augmented generation (rag)":30},[32,34,33,391,392,393,179,38,345,40,394,138,344,395,396,397,398,399],"Semantic Kernel","CrewAI","AutoGen","Embeddings","Fine-tuning","PEFT","API Integration","Workflow Orchestration","Distributed AI Architectures",{"agentic ai":30,"data science":30,"ai evaluation":29,"ai governance":29,"ai monitoring":29,"generative ai":30,"machine learning":30,"ai agent development":30,"multi-agent workflows":30,"ai solution deployment":30,"ai in regulated environments":29,"large language models (llms)":30,"natural language processing (nlp)":30},[190,95,402,53,314,137,403,404,405,59,60,406,407],"Natural Language Processing (NLP)","AI Agent Development","Multi-agent Workflows","AI Solution Deployment","AI Evaluation","AI in Regulated Environments",{"id":409,"slug":410,"title":411,"raw_title":11,"is_featured":12,"company":412,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":413,"processed_country_iso_code_gmaps":414,"processed_home_office":20,"processed_salary_min":415,"processed_salary_max":416,"processed_salary_currency":214,"processed_salary_source":24,"processed_working_hours":417,"processed_employment_types":27,"processed_it_skills":418,"processed_it_skills_labels":419,"processed_job_expertise_skills":430,"processed_job_expertise_skills_labels":431,"max_cpc":66,"actual_cpc":66},81614,"associate-director3367-allianz-insurance","Associate Director_3367",{"name":72,"slug":73,"logo_url":74},[],[211],4000000,6000000,[26],{"aws":29,"gcp":29,"rag":29,"azure":29,"genai":29,"mlops":29,"agents":29,"monitoring":29,"ai governance":29,"responsible ai":29,"llm integration":29,"embedding stores":29,"vector databases":29,"api orchestration":29,"agentic frameworks":29,"data harmonization":29,"orchestration tools":29,"automation pipelines":29,"solution architecture":29,"cloud-native platforms":29,"enterprise architecture":29},[420,421,85,87,422,423,424,425,426,90,91,92,40,427,357,428,429,59,100,88,197],"Enterprise Architecture","Solution Architecture","Agents","Automation Pipelines","API Orchestration","Data Harmonization","Cloud-Native Platforms","Embedding Stores","Orchestration Tools","LLM Integration",{"hiring":30,"runbooks":30,"resourcing":30,"kpi tracking":30,"demand shaping":30,"prioritization":30,"reuse practices":30,"risk management":30,"budget ownership":30,"people management":30,"career development":30,"sla\u002Fola management":30,"build-to-run handover":30,"continuous improvement":30,"technical team leadership":30,"insurance domain knowledge":29,"delivery portfolio management":30,"solution lifecycle management":30,"matrix organization experience":30,"regulated environment experience":29},[432,433,434,435,436,437,438,439,440,441,442,443,198,444,445,446,447,448,449,450],"Delivery Portfolio Management","Demand Shaping","Prioritization","Resourcing","Budget Ownership","Risk Management","Solution Lifecycle Management","Reuse Practices","Build-to-Run Handover","SLA\u002FOLA Management","Runbooks","KPI Tracking","People Management","Hiring","Career Development","Technical Team Leadership","Matrix Organization Experience","Insurance Domain Knowledge","Regulated Environment Experience",{"id":452,"slug":453,"title":454,"raw_title":11,"is_featured":12,"company":455,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":459,"processed_country_iso_code_gmaps":461,"processed_home_office":20,"processed_salary_min":171,"processed_salary_max":387,"processed_salary_currency":81,"processed_salary_source":24,"processed_working_hours":463,"processed_employment_types":27,"processed_it_skills":464,"processed_it_skills_labels":465,"processed_job_expertise_skills":476,"processed_job_expertise_skills_labels":477,"max_cpc":66,"actual_cpc":66},84215,"solution-architect-wb-ai-data-analytics-ing-hubs-romania-ing-hubs-bv-amsterdam-sucursala-bucuresti","Solution Architect - WB AI \u002F Data & Analytics @ING Hubs Romania",{"name":456,"slug":457,"logo_url":458},"ING Bank N. V. Amsterdam - Sucursala Bucuresti","ing-bank-n-v-amsterdam-sucursala-bucuresti","https:\u002F\u002Fwww.ing.de\u002Fbinaries\u002Fcontent\u002Fgallery\u002Fing-images\u002Fuber-uns\u002Fpresse\u002Fpressebilder\u002Fing_logo-72dpi_rgb.jpg",[460],"Bukarest",[462],"RO",[26],{"uml":29,"mlops":29,"llm ops":29,"archimate":29,"genai solutions":30,"model selection":30,"cloud ecosystems":29,"vector databases":30,"agentic workflows":30,"ci\u002Fcd integration":29,"rag architectures":30,"prompt orchestration":30,"ai platform capabilities":30,"llm integration patterns":30},[466,467,184,55,468,469,470,40,471,472,88,473,474,475],"GenAI Solutions","LLM Integration Patterns","Prompt Orchestration","Model Selection","AI Platform Capabilities","UML","ArchiMate","LLM Ops","CI\u002FCD Integration","Cloud Ecosystems",{"togaf":29,"data modeling":29,"technical design":30,"agile way of working":29,"regulatory compliance":29,"solution architecture":30,"architecture documentation":29,"wholesale banking knowledge":29,"service management processes":29,"it architecture methodologies":29},[421,478,479,480,481,482,483,61,371,484],"Technical Design","IT Architecture Methodologies","TOGAF","Service Management Processes","Agile Way of Working","Wholesale Banking Knowledge","Architecture Documentation",{"id":486,"slug":487,"title":488,"raw_title":11,"is_featured":12,"company":489,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":492,"processed_country_iso_code_gmaps":494,"processed_home_office":123,"processed_salary_min":496,"processed_salary_max":497,"processed_salary_currency":498,"processed_salary_source":24,"processed_working_hours":499,"processed_employment_types":27,"processed_it_skills":500,"processed_it_skills_labels":501,"processed_job_expertise_skills":515,"processed_job_expertise_skills_labels":516,"max_cpc":66,"actual_cpc":66},86136,"ai-full-stack-developer-python-ocbc-e2-power-shenzhen-co-ltd-3","AI Full Stack Developer (Python)",{"name":490,"slug":491,"logo_url":11},"OCBC e2 Power (Shenzhen) Co Ltd","ocbc-e2-power-shenzhen-co-ltd",[493],"Shenzhen",[495],"CN",300000,600000,"CNY",[26],{"git":29,"mcp":250,"rag":250,"vue":29,"ci\u002Fcd":29,"devin":29,"flask":29,"linux":29,"react":29,"cursor":29,"django":29,"docker":29,"python":30,"angular":29,"fastapi":29,"windsurf":29,"openshift":29,"kubernetes":29,"aws bedrock":250,"claude code":29,"restful api":30,"anthropic apis":250,"github copilot":29,"vector databases":250},[32,274,275,502,503,272,504,273,505,181,182,506,507,94,508,39,509,87,40,510,511,512,513,514],"Django","RESTful API","Vue","Linux","Kubernetes","OpenShift","AWS Bedrock","MCP","Claude Code","Devin","GitHub Copilot","Cursor","Windsurf",{"devops":29,"ai agents":250,"containerization":29,"automated testing":29,"agile methodologies":29,"platform engineering":29,"software development":30,"llm-based applications":250,"ai-assisted development":29,"cloud-native development":29,"microservices architecture":29,"financial services industry":250},[189,517,518,519,520,310,521,522,523,139,524,525],"Agile Methodologies","Microservices Architecture","Cloud-native Development","Containerization","Automated Testing","Platform Engineering","AI-assisted Development","LLM-based Applications","Financial Services Industry",{"id":527,"slug":528,"title":529,"raw_title":11,"is_featured":12,"company":530,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":533,"processed_country_iso_code_gmaps":535,"processed_home_office":20,"processed_salary_min":79,"processed_salary_max":537,"processed_salary_currency":23,"processed_salary_source":24,"processed_working_hours":538,"processed_employment_types":27,"processed_it_skills":539,"processed_it_skills_labels":540,"processed_job_expertise_skills":551,"processed_job_expertise_skills_labels":552,"max_cpc":66,"actual_cpc":66},81406,"senior-genai-software-developer-bank-of-montreal","Senior GenAI Software Developer",{"name":531,"slug":532,"logo_url":11},"Bank of Montreal","bank-of-montreal",[534],"Toronto",[536],"CA",150000,[26],{"sql":29,"java":250,"jira rovo":29,"azure openai":250,"restful apis":30,"aws agentcore":29,"microservices":30,"github copilot":29,"azure ai search":250,"cloud computing":30,"swagger\u002Fopenapi":29,"azure ai foundry":250,"vector databases":29,"prompt engineering":30,"microsoft copilot studio":250,"large language models (llms)":30,"model context protocol (mcp)":29,"retrieval-augmented generation (rag)":30},[135,344,541,512,542,543,544,178,545,137,138,40,546,46,547,548,549,550],"JIRA Rovo","AWS AgentCore","RESTful APIs","Swagger\u002FOpenAPI","Cloud Computing","Model Context Protocol (MCP)","Azure OpenAI","Azure AI Foundry","Azure AI Search","Microsoft Copilot Studio",{"mentoring":30,"ai governance":29,"responsible ai":29,"risk management":29,"troubleshooting":30,"version control":29,"ai\u002Fml engineering":30,"release management":29,"system integration":30,"agile methodologies":29,"root-cause analysis":30,"software development":30,"technical leadership":30,"solution architecture":30,"application engineering":30,"performance optimization":29,"secure software development":29,"quality assurance and testing":29,"test driven development (tdd)":29,"business requirements analysis":29,"software development lifecycle (sdlc)":30},[189,553,554,555,556,517,557,558,559,560,100,59,561,421,562,563,136,564,565,44,437],"Application Engineering","AI\u002FML Engineering","Technical Leadership","Mentoring","Software Development Lifecycle (SDLC)","Quality Assurance and Testing","Test Driven Development (TDD)","Secure Software Development","Business Requirements Analysis","System Integration","Release Management","Troubleshooting","Root-Cause Analysis",{"id":567,"slug":568,"title":569,"raw_title":11,"is_featured":12,"company":570,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":571,"processed_country_iso_code_gmaps":572,"processed_home_office":20,"processed_salary_min":172,"processed_salary_max":573,"processed_salary_currency":81,"processed_salary_source":24,"processed_working_hours":574,"processed_employment_types":27,"processed_it_skills":575,"processed_it_skills_labels":576,"processed_job_expertise_skills":584,"processed_job_expertise_skills_labels":585,"max_cpc":66,"actual_cpc":66},71040,"ai-factory-product-owner-mfd-allianz-insurance","AI Factory Product Owner (m\u002Ff\u002Fd)",{"name":72,"slug":73,"logo_url":74},[76],[78],120000,[26],{"llms":29,"finops tools":29,"rag patterns":29,"agent frameworks":29,"vector databases":29,"prompt management":29,"observability tools":29,"model routing\u002Fcaching":29,"api abstractions (mcp)":29},[86,577,578,40,579,580,581,582,583],"Agent Frameworks","RAG Patterns","Prompt Management","Model Routing\u002FCaching","API Abstractions (MCP)","Observability Tools","FinOps Tools",{"finops":30,"security":30,"compliance":30,"gtm strategy":29,"ai governance":30,"capacity planning":29,"product ownership":30,"vendor management":29,"kpi\u002Fokr definition":30,"product management":30,"platform reliability":30,"agile at scale (scrum\u002Fkanban)":30},[586,587,588,59,589,590,591,106,109,592,318,593],"Product Ownership","Product Management","Agile at Scale (Scrum\u002FKanban)","Compliance","Security","FinOps","Platform Reliability","GTM Strategy",{"id":595,"slug":596,"title":597,"raw_title":11,"is_featured":12,"company":598,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":599,"processed_country_iso_code_gmaps":601,"processed_home_office":20,"processed_salary_min":79,"processed_salary_max":80,"processed_salary_currency":81,"processed_salary_source":24,"processed_working_hours":603,"processed_employment_types":27,"processed_it_skills":604,"processed_it_skills_labels":605,"processed_job_expertise_skills":613,"processed_job_expertise_skills_labels":614,"max_cpc":66,"actual_cpc":66},71212,"forward-deployed-engineer3202-allianz-insurance","Forward Deployed Engineer_3202",{"name":72,"slug":73,"logo_url":74},[600],"PUTEAUX",[602],"FR",[26],{"apis":29,"ci\u002Fcd":29,"devops":29,"python":29,"data\u002Fml":29,"testing":29,"kubernetes":29,"observability":29,"secure coding":29,"llm frameworks":29,"agent frameworks":29,"containerization":29,"vector databases":29,"backend development":29,"frontend development":29,"infrastructure as code":29},[32,93,40,606,577,94,520,506,239,607,608,609,310,610,611,612],"LLM Frameworks","Backend Development","Frontend Development","Data\u002FML","Testing","Observability","Secure Coding",{"security":29,"software engineering":30,"regulatory compliance":29,"ai solution deployment":29,"reliability engineering":29,"cloud-native development":29},[306,405,615,61,590,45],"Cloud-Native Development",{"id":617,"slug":618,"title":619,"raw_title":11,"is_featured":12,"company":620,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":621,"processed_country_iso_code_gmaps":622,"processed_home_office":20,"processed_salary_min":79,"processed_salary_max":80,"processed_salary_currency":81,"processed_salary_source":24,"processed_working_hours":623,"processed_employment_types":27,"processed_it_skills":624,"processed_it_skills_labels":625,"processed_job_expertise_skills":636,"processed_job_expertise_skills_labels":637,"max_cpc":66,"actual_cpc":66},70847,"ai-platform-engineer-mfd3104-allianz-insurance","AI Platform Engineer (m\u002Ff\u002Fd)_3104",{"name":72,"slug":73,"logo_url":74},[76],[78],[26],{"go":29,"rag":30,"ci\u002Fcd":30,"mlops":30,"llmops":30,"python":30,"ai finops":30,"terraform":30,"ai gateway":30,"kubernetes":30,"networking":30,"typescript":29,"ai frameworks":30,"observability":30,"sre practices":30,"mcp interfaces":30,"embedding stores":30,"machine learning":29,"vector databases":30,"prompt management":30,"cloud-native infrastructure":30,"identity and risk management":30},[506,32,271,626,222,94,88,627,40,427,628,579,87,629,630,611,631,632,633,634,635,95],"Go","LLMOps","AI Frameworks","MCP Interfaces","AI Gateway","SRE Practices","Cloud-native Infrastructure","Networking","Identity and Risk Management","AI FinOps",{"sdks":30,"caching":30,"spec kits":30,"model routing":30,"risk recovery":30,"slo management":30,"usage metering":30,"standardization":30,"quota management":30,"capacity planning":30,"cost optimization":30,"incident response":30,"skills registries":30,"policy enforcement":30,"release automation":30,"runtime operations":30,"platform governance":30,"shared rag services":30,"developer experience":30,"lifecycle management":30,"ai platform engineering":30,"reliability engineering":30,"scalability optimization":30,"ai tool landscape curation":30,"compliance and safety guardrails":30},[638,639,640,318,641,642,643,644,45,317,645,646,647,648,649,650,651,652,653,654,655,656,657,658,659],"AI Platform Engineering","Platform Governance","Compliance and Safety Guardrails","Release Automation","Risk Recovery","Cost Optimization","Scalability Optimization","SLO Management","Usage Metering","Quota Management","Policy Enforcement","AI Tool Landscape Curation","Lifecycle Management","Standardization","Developer Experience","Runtime Operations","Model Routing","Caching","Shared RAG Services","Skills Registries","Spec Kits","SDKs",{"id":661,"slug":662,"title":663,"raw_title":11,"is_featured":12,"company":664,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":667,"processed_country_iso_code_gmaps":669,"processed_home_office":20,"processed_salary_min":387,"processed_salary_max":671,"processed_salary_currency":672,"processed_salary_source":24,"processed_working_hours":673,"processed_employment_types":27,"processed_it_skills":674,"processed_it_skills_labels":675,"processed_job_expertise_skills":677,"processed_job_expertise_skills_labels":678,"max_cpc":66,"actual_cpc":66},75945,"vice-president-senior-ai-engineer-mufg-united-kingdom-btmu","Vice President, Senior AI Engineer",{"name":665,"slug":666,"logo_url":11},"MUFG - United Kingdom (BTMU)","mufg-united-kingdom-btmu",[668],"London",[670],"GB",130000,"GBP",[26],{"aws":29,"mcp":29,"azure":30,"python":30,"azure ai":30,"langchain":30,"langgraph":30,"ci\u002Fcd pipelines":29,"vector databases":30},[32,90,91,33,34,179,509,40,676],"CI\u002FCD Pipelines",{"data science":30,"generative ai":30,"responsible ai":30,"data governance":30,"machine learning":30,"model evaluation":30,"prompt engineering":30,"model risk management":30,"technology evaluation":30,"secure by design (sbd)":29,"artificial intelligence":30,"architectural documentation":30,"support services (l1\u002Fl2\u002Fl3)":29,"financial services regulations":29,"technical standards definition":30,"architecture review board (arb)":29,"return on investment (roi) analysis":30,"retrieval augmented generation (rag)":30,"systems development lifecycle (sdlc)":30,"data protection impact assessment (dpia)":29},[679,95,190,53,680,344,146,681,682,683,684,324,685,100,686,687,193,688,689,690],"Artificial Intelligence","Retrieval Augmented Generation (RAG)","Systems Development Lifecycle (SDLC)","Secure by Design (SbD)","Architecture Review Board (ARB)","Data Protection Impact Assessment (DPIA)","Model Risk Management","Technical Standards Definition","Architectural Documentation","Return on Investment (ROI) Analysis","Support Services (L1\u002FL2\u002FL3)","Financial Services Regulations",{"id":692,"slug":693,"title":694,"raw_title":11,"is_featured":12,"company":695,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":698,"processed_country_iso_code_gmaps":700,"processed_home_office":20,"processed_salary_min":497,"processed_salary_max":702,"processed_salary_currency":703,"processed_salary_source":24,"processed_working_hours":704,"processed_employment_types":27,"processed_it_skills":705,"processed_it_skills_labels":706,"processed_job_expertise_skills":710,"processed_job_expertise_skills_labels":711,"max_cpc":66,"actual_cpc":66},69576,"data-scientist-associate-ai-performance-evolution-ciudad-de-mexico-bbva-mexico-sa","Data Scientist Associate – AI Performance & Evolution (Ciudad de México)",{"name":696,"slug":697,"logo_url":11},"BBVA MÉXICO S.A.","bbva-mexico-sa",[699],"Mexiko-Stadt",[701],"MX",900000,"MXN",[26],{"rag":29,"llms":29,"ci\u002Fcd":29,"evals":29,"mlops":29,"pytorch":29,"xgboost":29,"embeddings":29,"tensorflow":29,"scikit-learn":29,"semantic search":29,"vector databases":29},[88,94,707,131,133,134,86,87,394,708,40,709],"scikit-learn","Semantic Search","Evals",{"genai":29,"monitoring":29,"ai solutions":30,"data science":30,"version control":29,"incident management":29,"root cause analysis":29},[190,712,85,197,713,714,136],"AI Solutions","Incident Management","Root Cause Analysis",{"id":716,"slug":717,"title":718,"raw_title":11,"is_featured":12,"company":719,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":722,"processed_country_iso_code_gmaps":723,"processed_home_office":20,"processed_salary_min":724,"processed_salary_max":725,"processed_salary_currency":23,"processed_salary_source":24,"processed_working_hours":726,"processed_employment_types":27,"processed_it_skills":727,"processed_it_skills_labels":728,"processed_job_expertise_skills":737,"processed_job_expertise_skills_labels":738,"max_cpc":66,"actual_cpc":66},88428,"data-engineer-ii-genai-travelers-indemnity-co","Data Engineer II, GenAI",{"name":720,"slug":721,"logo_url":11},"Travelers Indemnity Co","travelers-indemnity-co",[335],[19],126500,208700,[26],{"aws":30,"dbt":30,"sql":30,"python":30,"snowflake":30,"databricks":30,"data quality":29,"data security":29,"data pipelines":30,"cloud platforms":30,"data governance":29,"vector databases":30,"data transformation":30,"embedding strategies":30,"large language model apis":30,"model context protocol (mcp)":30,"agent orchestration frameworks":30,"retrieval-augmented generation (rag)":30},[91,729,342,730,32,135,731,138,40,732,546,733,734,349,735,324,736,322],"Databricks","dbt","Large Language Model APIs","Embedding Strategies","Agent Orchestration Frameworks","Cloud Platforms","Data Transformation","Data Security",{"data analysis":30,"data modeling":30,"data management":30,"system analysis":30,"data engineering":30,"domain expertise":29,"data pipeline design":30,"cloud-native architecture":30,"multi-agent ai applications":30,"software engineering practices":30},[232,739,740,741,742,743,744,745,746,371],"Data Pipeline Design","Cloud-Native Architecture","Multi-Agent AI Applications","Data Analysis","Data Management","Software Engineering Practices","Domain Expertise","System Analysis",{"id":748,"slug":749,"title":750,"raw_title":11,"is_featured":12,"company":751,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":754,"processed_country_iso_code_gmaps":756,"processed_home_office":20,"processed_salary_min":757,"processed_salary_max":415,"processed_salary_currency":214,"processed_salary_source":24,"processed_working_hours":758,"processed_employment_types":27,"processed_it_skills":759,"processed_it_skills_labels":760,"processed_job_expertise_skills":787,"processed_job_expertise_skills_labels":788,"max_cpc":66,"actual_cpc":796},78821,"ind-senior-engineer-data-hartford-global-services-private-limited","IND Senior Engineer, Data",{"name":752,"slug":753,"logo_url":11},"Hartford Global Services Private Limited","hartford-global-services-private-limited",[755],"Hyderabad",[211],2500000,[26],{"a2a":30,"aws":30,"mcp":30,"rdf":30,"sql":30,"azure":30,"ci\u002Fcd":30,"neo4j":30,"nosql":30,"spark":30,"aws s3":30,"cypher":30,"docker":30,"python":30,"sparql":30,"aws ec2":30,"mongodb":30,"pytorch":29,"big data":30,"dynamodb":30,"data lake":30,"data mesh":30,"langchain":30,"langgraph":30,"snowflake":30,"aws lambda":30,"kubernetes":30,"tensorflow":29,"aws kinesis":30,"data fabric":30,"apache kafka":30,"document dbs":30,"etl\u002Felt tools":30,"gcp vertex ai":30,"spanner graph":30,"amazon neptune":30,"aws opensearch":30,"graph databases":30,"spark streaming":30,"vector databases":30,"google cloud platform":30},[761,762,763,135,764,342,765,94,766,91,276,90,32,767,768,769,770,182,506,134,133,40,771,772,773,774,775,776,777,778,779,780,781,782,33,34,509,783,784,785,786],"Apache Kafka","AWS Kinesis","Spark Streaming","NoSQL","ETL\u002FELT tools","Big Data","Spark","Data Mesh","Data Lake","Data Fabric","Graph Databases","Document DBs","AWS OpenSearch","GCP Vertex AI","Neo4j","Spanner Graph","Amazon Neptune","MongoDB","DynamoDB","AWS Lambda","AWS S3","AWS EC2","A2A","Cypher","SPARQL","RDF",{"devops":30,"data lakes":30,"data domains":30,"data lineage":30,"data quality":30,"scaled agile":30,"data products":30,"generative ai":30,"data catalogue":30,"data governance":30,"cloud technology":30,"data engineering":30,"data integration":30,"data warehousing":30,"knowledge graphs":30,"data architecture":30,"semantic modeling":30,"prompt engineering":30,"business intelligence":30,"reliability engineering":30,"synthetic data generation":30,"ai-driven data engineering":30,"insurance domain knowledge":29,"retrieval-augmented generation (rag)":30},[232,360,350,352,351,789,374,353,790,53,138,344,791,41,792,324,322,323,793,794,310,45,795,449],"Data Domains","Cloud Technology","Semantic Modeling","Synthetic Data Generation","Data Catalogue","AI-driven Data Engineering","Scaled Agile",0.5,{"industry":798,"employment_type":846,"expertise_skills":853,"it_skills":916,"salary_currency":986,"processed_working_hours":1007},[799,803,807,811,815,819,823,826,829,832,834,837,840,843],{"key":800,"label":801,"count":802},"insurance","Insurance",39,{"key":804,"label":805,"count":806},"financial services","Financial Services",35,{"key":808,"label":809,"count":810},"banking","Banking",19,{"key":812,"label":813,"count":814},"financial markets infrastructure","Financial Markets Infrastructure",12,{"key":816,"label":817,"count":818},"data","Data",7,{"key":820,"label":821,"count":822},"data provider","Data Provider",5,{"key":824,"label":825,"count":30},"asset management","Asset Management",{"key":827,"label":828,"count":250},"property","Property",{"key":830,"label":831,"count":250},"casualty insurance","Casualty Insurance",{"key":833,"label":437,"count":250},"risk management",{"key":835,"label":836,"count":66},"venture capital","Venture Capital",{"key":838,"label":839,"count":66},"credit union","Credit Union",{"key":841,"label":842,"count":66},"information technology","Information Technology",{"key":844,"label":845,"count":66},"alternative investments","Alternative Investments",[847,850],{"key":27,"label":848,"count":849},"PERMANENT",90,{"key":851,"label":852,"count":66},"contract","CONTRACT",[854,858,861,864,867,869,872,876,878,881,883,885,888,891,894,896,898,900,903,905,907,909,911,914],{"key":855,"label":856,"slug":855,"count":857},"ai-governance","Ai Governance",24,{"key":859,"label":306,"slug":859,"count":860},"software-engineering",17,{"key":862,"label":863,"slug":862,"count":860},"generative-ai","Generative Ai",{"key":865,"label":232,"slug":865,"count":866},"data-engineering",16,{"key":868,"label":61,"slug":868,"count":866},"regulatory-compliance",{"key":870,"label":344,"slug":870,"count":871},"prompt-engineering",15,{"key":873,"label":874,"slug":873,"count":875},"responsible-ai","Responsible Ai",14,{"key":877,"label":437,"slug":877,"count":875},"risk-management",{"key":879,"label":324,"slug":879,"count":880},"data-governance",13,{"key":882,"label":95,"slug":882,"count":814},"machine-learning",{"key":884,"label":589,"slug":884,"count":814},"compliance",{"key":886,"label":517,"slug":886,"count":887},"agile-methodologies",11,{"key":889,"label":55,"slug":889,"count":890},"agentic-workflows",9,{"key":892,"label":893,"slug":892,"count":890},"devops","Devops",{"key":895,"label":420,"slug":895,"count":890},"enterprise-architecture",{"key":897,"label":322,"slug":897,"count":890},"data-quality",{"key":899,"label":685,"slug":899,"count":890},"model-risk-management",{"key":901,"label":234,"slug":901,"count":902},"system-design",8,{"key":904,"label":421,"slug":904,"count":902},"solution-architecture",{"key":906,"label":371,"slug":906,"count":902},"data-modeling",{"key":908,"label":350,"slug":908,"count":818},"data-warehousing",{"key":910,"label":146,"slug":910,"count":818},"model-evaluation",{"key":912,"label":913,"slug":912,"count":818},"agentic-ai","Agentic Ai",{"key":915,"label":611,"slug":915,"count":818},"observability",[917,919,922,926,930,934,937,941,944,947,950,953,956,958,962,965,968,970,972,975,976,979,981,983],{"key":918,"label":40,"slug":918,"count":5},"vector-databases",{"key":920,"label":32,"slug":920,"count":921},"python",72,{"key":923,"label":924,"slug":923,"count":925},"cicd","Ci\u002FCd",48,{"key":927,"label":928,"slug":927,"count":929},"aws","Aws",36,{"key":931,"label":932,"slug":931,"count":933},"rag","Rag",33,{"key":935,"label":936,"slug":935,"count":933},"langchain","Langchain",{"key":938,"label":939,"slug":938,"count":940},"ms-azure","MS Azure",31,{"key":942,"label":506,"slug":942,"count":943},"kubernetes",27,{"key":945,"label":135,"slug":945,"count":946},"sql",26,{"key":948,"label":46,"slug":948,"count":949},"java",25,{"key":951,"label":952,"slug":951,"count":857},"mlops","Mlops",{"key":954,"label":182,"slug":954,"count":955},"docker",23,{"key":862,"label":863,"slug":862,"count":957},22,{"key":959,"label":960,"slug":959,"count":961},"langgraph","Langgraph",20,{"key":963,"label":964,"slug":963,"count":871},"llms","Llms",{"key":966,"label":967,"slug":966,"count":871},"gcp","Gcp",{"key":969,"label":222,"slug":969,"count":875},"terraform",{"key":971,"label":342,"slug":971,"count":880},"snowflake",{"key":973,"label":974,"slug":973,"count":814},"github-copilot","Github Copilot",{"key":870,"label":344,"slug":870,"count":814},{"key":977,"label":978,"slug":977,"count":887},"kafka","Kafka",{"key":980,"label":181,"slug":980,"count":887},"git",{"key":982,"label":41,"slug":982,"count":887},"knowledge-graphs",{"key":984,"label":985,"slug":984,"count":887},"mcp","Mcp",[987,989,991,993,995,996,998,999,1000,1002,1004,1006],{"key":23,"label":23,"count":988},37,{"key":81,"label":81,"count":990},18,{"key":214,"label":214,"count":992},10,{"key":994,"label":994,"count":902},"SGD",{"key":672,"label":672,"count":818},{"key":997,"label":997,"count":30},"CAD",{"key":498,"label":498,"count":250},{"key":703,"label":703,"count":66},{"key":1001,"label":1001,"count":66},"PHP",{"key":1003,"label":1003,"count":66},"BRL",{"key":1005,"label":1005,"count":66},"TRY",{"key":126,"label":126,"count":66},[1008,1009],{"key":26,"label":26,"count":5},{"key":1010,"label":1010,"count":250},"PART_TIME",{"total":66,"jobs":1012},[]]