[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"seo-content-skill-langchain-in":3,"job-search-\u002Fde-in\u002Fjobs-by-skill\u002Flangchain?page=1":8,"skill-page-filters-\u002Fde-in\u002Fjobs-by-skill\u002Flangchain?page=1":731,"featured-jobs-\u002Fde-in\u002Fjobs-by-skill\u002Flangchain?page=1":890},{"image_path":4,"content_de":5,"content_en":5,"composite_key":6,"last_updated":7},"\u002Fimages\u002Fskill\u002Flangchain.webp",null,"skill:langchain:in","2026-08-17T09:06:27.231574+02:00",{"total":9,"jobs":10},24,[11,101,117,130,183,207,255,307,343,374,400,438,487,534,560,589,627,651,686,707],{"id":12,"slug":13,"title":14,"raw_title":5,"is_featured":15,"company":16,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":19,"processed_country_iso_code_gmaps":21,"processed_home_office":23,"processed_salary_min":24,"processed_salary_max":25,"processed_salary_currency":26,"processed_salary_source":27,"processed_working_hours":28,"processed_employment_types":30,"processed_it_skills":31,"processed_it_skills_labels":34,"processed_job_expertise_skills":74,"processed_job_expertise_skills_labels":75,"max_cpc":100,"actual_cpc":100},99306,"indstaff-software-engineer-ai-hartford-global-services-private-limited-4","INDStaff Software Engineer - AI",false,{"name":17,"slug":18,"logo_url":5},"Hartford Global Services Private Limited","hartford-global-services-private-limited",[20],"Hyderabad",[22],"IN","onsite",3000000,5000000,"INR","estimated",[29],"FULL_TIME","permanent",{"c#":32,"aws":32,"gcp":32,"sql":32,".net":32,"grpc":32,"java":32,"azure":32,"nosql":32,"react":32,"claude":33,"crewai":33,"cursor":33,"django":32,"docker":32,"openai":33,"python":33,"vue.js":32,"angular":32,"autogen":33,"fastapi":32,"graphql":32,"jenkins":32,"node.js":32,"chromadb":32,"pgvector":32,"pinecone":32,"weaviate":32,"anthropic":33,"langchain":33,"kubernetes":32,"llamaindex":33,"typescript":32,"aws bedrock":33,"restful apis":33,"github actions":32,"github copilot":33,"semantic kernel":33,"google vertex ai":33},3,4,[35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73],"Python","SQL","NoSQL","RESTful APIs","GraphQL","gRPC","Docker","Kubernetes","Jenkins","GitHub Actions","AWS","GCP","Azure","LangChain","Semantic Kernel","AutoGen","CrewAI","LlamaIndex","OpenAI","Anthropic","Google Vertex AI","AWS Bedrock","React","Angular","Vue.js","TypeScript","Node.js","Java","C#",".NET","FastAPI","Django","Pinecone","Weaviate","pgvector","ChromaDB","GitHub Copilot","Cursor","Claude",{"ci\u002Fcd":33,"mlops":33,"llmops":33,"testing":33,"ai safety":32,"embeddings":33,"fine-tuning":33,"ai governance":32,"observability":33,"rag pipelines":33,"vector search":33,"api development":33,"model evaluation":33,"agentic workflows":33,"ai\u002Fml engineering":33,"prompt engineering":33,"ai coding assistants":33,"architecture reviews":32,"software development":33,"intelligent automation":33,"technical documentation":32,"event-driven integrations":33,"multi-model orchestration":33,"cloud-native ai infrastructure":33},[76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99],"AI\u002FML Engineering","Software Development","RAG Pipelines","Agentic Workflows","Multi-model Orchestration","Intelligent Automation","Prompt Engineering","Fine-tuning","Embeddings","Vector Search","MLOps","LLMOps","CI\u002FCD","API Development","Event-driven Integrations","AI Safety","AI Governance","Model Evaluation","Testing","Cloud-native AI Infrastructure","Observability","AI Coding Assistants","Technical Documentation","Architecture Reviews",1,{"id":102,"slug":103,"title":14,"raw_title":5,"is_featured":15,"company":104,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":105,"processed_country_iso_code_gmaps":106,"processed_home_office":23,"processed_salary_min":24,"processed_salary_max":25,"processed_salary_currency":26,"processed_salary_source":27,"processed_working_hours":107,"processed_employment_types":30,"processed_it_skills":108,"processed_it_skills_labels":109,"processed_job_expertise_skills":111,"processed_job_expertise_skills_labels":112,"max_cpc":100,"actual_cpc":100},99303,"indstaff-software-engineer-ai-hartford-global-services-private-limited-2",{"name":17,"slug":18,"logo_url":5},[20],[22],[29],{"c#":32,"aws":32,"gcp":32,"sql":32,".net":32,"grpc":32,"java":32,"azure":32,"nosql":32,"react":32,"claude":32,"crewai":32,"cursor":32,"django":32,"docker":32,"openai":32,"python":33,"vue.js":32,"angular":32,"autogen":32,"fastapi":32,"graphql":32,"jenkins":32,"node.js":32,"anthropic":32,"langchain":32,"kubernetes":32,"llamaindex":32,"typescript":32,"aws bedrock":32,"restful apis":33,"github actions":32,"github copilot":32,"semantic kernel":32,"google vertex ai":32,"vector databases":32},[35,62,60,61,63,64,57,58,59,65,66,38,39,40,36,37,110,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,71,72,73],"Vector Databases",{"ci\u002Fcd":32,"mlops":32,"llmops":32,"testing":32,"ai safety":32,"embeddings":32,"fine-tuning":32,"rag pipelines":33,"vector search":32,"data pipelines":32,"api development":33,"llm integration":33,"ai orchestration":32,"model evaluation":32,"agentic workflows":33,"ai\u002Fml engineering":33,"prompt engineering":33,"ai coding assistants":32,"cloud infrastructure":32,"software development":33},[76,77,113,78,79,82,83,84,85,86,87,114,89,115,88,91,93,116,97,94],"LLM Integration","AI Orchestration","Cloud Infrastructure","Data Pipelines",{"id":118,"slug":119,"title":14,"raw_title":5,"is_featured":15,"company":120,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":121,"processed_country_iso_code_gmaps":122,"processed_home_office":23,"processed_salary_min":24,"processed_salary_max":25,"processed_salary_currency":26,"processed_salary_source":27,"processed_working_hours":123,"processed_employment_types":30,"processed_it_skills":124,"processed_it_skills_labels":125,"processed_job_expertise_skills":127,"processed_job_expertise_skills_labels":128,"max_cpc":100,"actual_cpc":100},99304,"indstaff-software-engineer-ai-hartford-global-services-private-limited-3",{"name":17,"slug":18,"logo_url":5},[20],[22],[29],{"aws":32,"gcp":32,"sql":32,"grpc":32,"java":32,"azure":32,"nosql":32,"react":32,"claude":33,"crewai":33,"cursor":33,"django":32,"docker":32,"openai":33,"python":33,"vue.js":32,"angular":32,"autogen":33,"c#\u002F.net":32,"fastapi":32,"graphql":32,"jenkins":32,"node.js":32,"chromadb":32,"pgvector":32,"pinecone":32,"weaviate":32,"anthropic":33,"langchain":33,"kubernetes":32,"llamaindex":33,"typescript":32,"aws bedrock":33,"restful apis":33,"github actions":32,"github copilot":33,"semantic kernel":33,"google vertex ai":33},[35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,67,68,69,70,57,58,59,60,61,62,126,65,66,71,72,73],"C#\u002F.NET",{"ci\u002Fcd":32,"mlops":32,"llmops":32,"ai safety":32,"embeddings":32,"fine-tuning":32,"observability":32,"rag pipelines":33,"vector search":32,"api development":33,"ai orchestration":33,"model evaluation":32,"agentic workflows":33,"ai\u002Fml engineering":33,"prompt engineering":33,"architecture reviews":32,"cloud infrastructure":32,"software development":33,"technical documentation":32,"ai-augmented development":33},[76,77,82,83,84,85,86,87,114,79,78,93,91,89,115,88,96,129,98,99],"AI-Augmented Development",{"id":131,"slug":132,"title":133,"raw_title":5,"is_featured":15,"company":134,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":137,"processed_country_iso_code_gmaps":139,"processed_home_office":140,"processed_salary_min":24,"processed_salary_max":25,"processed_salary_currency":26,"processed_salary_source":27,"processed_working_hours":141,"processed_employment_types":30,"processed_it_skills":142,"processed_it_skills_labels":144,"processed_job_expertise_skills":160,"processed_job_expertise_skills_labels":161,"max_cpc":100,"actual_cpc":100},92326,"lead-engineer-data-ingestion-vp-f337-deutsche-india-private-limited-pune-branch","Lead Engineer, Data Ingestion, VP",{"name":135,"slug":136,"logo_url":5},"F337 Deutsche India Private Limited, Pune Branch","f337-deutsche-india-private-limited-pune-branch",[138],"Pune",[22],"hybrid",[29],{"git":33,"gke":32,"sql":33,"java":33,"ci\u002Fcd":33,"kafka":143,"trino":143,"polars":143,"pyspark":33,"bigquery":32,"dataproc":32,"cloud run":32,"langchain":143,"langgraph":143,"openshift":33,"kubernetes":33,"spring boot":33,"apache spark":33,"github copilot":143,"gemini code assist":143,"google cloud platform":33},2,[62,145,146,147,42,148,149,150,151,152,153,36,88,154,71,155,48,156,157,158,159],"Spring Boot","Apache Spark","PySpark","OpenShift","Google Cloud Platform","Cloud Run","Dataproc","GKE","BigQuery","Git","Gemini Code Assist","LangGraph","Polars","Trino","Kafka",{"apis":33,"finops":143,"finance":32,"treasury":32,"data lineage":143,"data modeling":33,"microservices":33,"risk management":32,"data engineering":33,"automated testing":33,"production support":33,"secure engineering":33,"architecture design":33,"metadata management":143,"regulatory reporting":32,"software engineering":33,"technical leadership":33,"distributed processing":33,"data quality frameworks":143,"event-driven integration":33,"site reliability engineering":143},[162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182],"Software Engineering","Data Engineering","Technical Leadership","Distributed Processing","Data Modeling","APIs","Microservices","Event-Driven Integration","Automated Testing","Secure Engineering","Production Support","Architecture Design","Regulatory Reporting","Risk Management","Finance","Treasury","Site Reliability Engineering","FinOps","Data Lineage","Metadata Management","Data Quality Frameworks",{"id":184,"slug":185,"title":186,"raw_title":5,"is_featured":15,"company":187,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":190,"processed_country_iso_code_gmaps":192,"processed_home_office":23,"processed_salary_min":193,"processed_salary_max":194,"processed_salary_currency":26,"processed_salary_source":27,"processed_working_hours":195,"processed_employment_types":30,"processed_it_skills":196,"processed_it_skills_labels":197,"processed_job_expertise_skills":202,"processed_job_expertise_skills_labels":203,"max_cpc":100,"actual_cpc":100},89417,"software-engineer-senior-consultant-i-allstate-india-pvt-ltd","Software Engineer Senior Consultant I",{"name":188,"slug":189,"logo_url":5},"Allstate India Pvt Ltd","allstate-india-pvt-ltd",[191],"Bengaluru",[22],1500000,2500000,[29],{"aws":143,"gcp":143,"llm":33,"rag":32,"java":33,"azure":32,"ci\u002Fcd":32,"react":143,"docker":32,"openai":32,"python":33,"angular":143,"fastapi":32,"node.js":32,"langchain":33,"kubernetes":32,"spring boot":33,"hugging face":32,"restful apis":33,"generative ai":33,"microservices":33,"vector databases":32,"prompt engineering":32},[62,145,35,61,65,38,168,198,53,199,48,200,201,82,110,41,42,88,47,45,46,57,58],"Generative AI","Hugging Face","LLM","RAG",{"mlops":143,"model deployment":143,"backend development":33,"asynchronous processing":32},[204,205,86,206],"Backend Development","Asynchronous Processing","Model Deployment",{"id":208,"slug":209,"title":210,"raw_title":5,"is_featured":15,"company":211,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":214,"processed_country_iso_code_gmaps":216,"processed_home_office":23,"processed_salary_min":24,"processed_salary_max":25,"processed_salary_currency":26,"processed_salary_source":27,"processed_working_hours":217,"processed_employment_types":30,"processed_it_skills":218,"processed_it_skills_labels":219,"processed_job_expertise_skills":238,"processed_job_expertise_skills_labels":239,"max_cpc":100,"actual_cpc":100},95693,"lead-software-engineer-mufg-global-service-private-limited","Lead Software Engineer",{"name":212,"slug":213,"logo_url":5},"MUFG Global Service Private Limited","mufg-global-service-private-limited",[215],"Bangalore",[22],[29],{"aws":33,"emr":32,"etl":33,"rag":33,"sql":33,"hive":32,"idmc":33,"java":32,"jira":32,"ci\u002Fcd":32,"kafka":32,"spark":32,"hadoop":32,"python":33,"autosys":32,"kinesis":32,"pgvector":33,"data lake":33,"er\u002Fstudio":32,"langchain":32,"terraform":32,"llamaindex":32,"postgresql":33,"generative ai":33,"amazon bedrock":33,"amazon sagemaker":32,"data warehousing":33,"vector databases":33,"amazon opensearch":33,"unix\u002Flinux shell scripting":33},[35,62,36,220,45,221,222,223,224,198,201,110,225,226,69,48,52,227,228,229,88,230,159,231,232,233,234,235,236,237],"UNIX\u002FLinux Shell Scripting","IDMC","ETL","Data Warehousing","Data Lake","Amazon OpenSearch","PostgreSQL","Amazon Bedrock","Amazon SageMaker","Terraform","Spark","Hadoop","Hive","Kinesis","EMR","JIRA","Autosys","ER\u002FStudio",{"data quality":33,"ai governance":33,"data modeling":33,"data governance":33,"semantic search":33,"data engineering":33,"data integration":33,"technical design":33,"agile methodology":32,"cloud architecture":33,"performance tuning":33,"production support":33,"prompt engineering":33,"root cause analysis":33,"database engineering":33,"document intelligence":33,"model risk management":33,"waterfall methodology":32,"infrastructure as code":32,"requirements gathering":33},[163,240,241,166,242,243,82,244,245,92,246,247,248,249,250,251,172,252,253,254],"Data Integration","Database Engineering","Performance Tuning","Data Quality","Semantic Search","Document Intelligence","Model Risk Management","Data Governance","Cloud Architecture","Infrastructure as Code","Agile Methodology","Waterfall Methodology","Root Cause Analysis","Technical Design","Requirements Gathering",{"id":256,"slug":257,"title":258,"raw_title":5,"is_featured":15,"company":259,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":260,"processed_country_iso_code_gmaps":261,"processed_home_office":140,"processed_salary_min":194,"processed_salary_max":262,"processed_salary_currency":26,"processed_salary_source":27,"processed_working_hours":263,"processed_employment_types":30,"processed_it_skills":264,"processed_it_skills_labels":265,"processed_job_expertise_skills":289,"processed_job_expertise_skills_labels":290,"max_cpc":100,"actual_cpc":100},99305,"ind-staff-engineer-data-hartford-global-services-private-limited-2","IND Staff Engineer, Data",{"name":17,"slug":18,"logo_url":5},[20],[22],4000000,[29],{"a2a":32,"aws":33,"gcp":33,"mcp":32,"rdf":32,"sql":33,"azure":33,"ci\u002Fcd":33,"neo4j":33,"nosql":33,"cypher":32,"docker":33,"python":33,"sparql":32,"etl\u002Felt":33,"mongodb":33,"pytorch":32,"big data":33,"dynamodb":33,"amazon s3":33,"langchain":33,"langgraph":33,"snowflake":33,"amazon ec2":33,"aws lambda":33,"kubernetes":33,"tensorflow":32,"aws kinesis":33,"apache kafka":33,"apache spark":33,"gcp vertex ai":33,"spanner graph":32,"amazon neptune":33,"aws opensearch":33,"spark streaming":33},[35,36,37,266,267,88,268,45,46,47,146,269,270,271,41,42,272,273,274,275,276,277,278,48,156,279,280,281,282,283,284,285,286,287,288],"Snowflake","ETL\u002FELT","Big Data","Apache Kafka","AWS Kinesis","Spark Streaming","PyTorch","TensorFlow","Neo4j","Amazon Neptune","RDF","SPARQL","Cypher","AWS Lambda","Amazon S3","Amazon EC2","MCP","A2A","AWS OpenSearch","GCP Vertex AI","Spanner Graph","MongoDB","DynamoDB",{"devops":33,"data mesh":33,"data lakes":33,"data fabric":33,"data catalog":33,"data lineage":33,"data quality":33,"scaled agile":33,"data products":33,"generative ai":33,"data governance":33,"data engineering":33,"data integration":33,"data warehousing":33,"knowledge graphs":33,"agentic solutions":33,"data architecture":33,"semantic modeling":33,"prompt engineering":33,"business intelligence":33,"reliability engineering":33,"synthetic data generation":33,"insurance domain knowledge":32,"retrieval-augmented generation (rag)":33},[163,291,223,240,292,293,294,295,296,247,243,180,297,198,298,82,299,300,301,302,303,304,305,306],"Data Architecture","Data Lakes","Data Mesh","Data Fabric","Data Products","Business Intelligence","Data Catalog","Retrieval-Augmented Generation (RAG)","Semantic Modeling","Knowledge Graphs","Synthetic Data Generation","Agentic Solutions","Scaled Agile","DevOps","Reliability Engineering","Insurance Domain Knowledge",{"id":308,"slug":309,"title":310,"raw_title":5,"is_featured":15,"company":311,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":312,"processed_country_iso_code_gmaps":313,"processed_home_office":140,"processed_salary_min":194,"processed_salary_max":262,"processed_salary_currency":26,"processed_salary_source":27,"processed_working_hours":314,"processed_employment_types":30,"processed_it_skills":315,"processed_it_skills_labels":316,"processed_job_expertise_skills":328,"processed_job_expertise_skills_labels":329,"max_cpc":100,"actual_cpc":100},92353,"senior-engineer-avp-f337-deutsche-india-private-limited-pune-branch-2","Senior Engineer, AVP",{"name":135,"slug":136,"logo_url":5},[138],[22],[29],{"gcp":33,"jira":32,"gemini":32,"hadoop":32,"hp alm":32,"python":33,"pyspark":33,"bigquery":32,"dataflow":32,"dataproc":32,"langchain":32,"terraform":32,"vertex ai":33,"llamaindex":32,"servicenow":32,"document ai":32,"apache spark":33,"agent builder":32,"apache airflow":32,"github copilot":32,"vector databases":143,"vertex ai pipelines":32},[35,147,146,231,46,317,153,151,318,319,320,321,322,48,52,229,323,324,325,326,327,110],"Vertex AI","Dataflow","Agent Builder","Document AI","Gemini","Github Copilot","Apache Airflow","Vertex AI Pipelines","HP ALM","Jira","ServiceNow",{"ci\u002Fcd":32,"mlops":32,"dataops":32,"deep learning":32,"llm evaluation":32,"agile processes":33,"machine learning":33,"prompt engineering":32,"root cause analysis":32,"infrastructure as code":32,"workflow orchestration":32,"etl\u002Felt pipeline design":33,"query performance tuning":32,"ai ethics and data privacy":32,"financial services compliance":32,"software development lifecycle (sdlc)":33},[330,331,332,86,333,88,334,335,336,337,249,338,339,340,341,342],"ETL\u002FELT pipeline design","Machine Learning","Deep Learning","DataOps","Software Development Lifecycle (SDLC)","Agile processes","AI ethics and data privacy","Financial Services compliance","Workflow orchestration","Prompt engineering","LLM evaluation","Root cause analysis","Query performance tuning",{"id":344,"slug":345,"title":346,"raw_title":5,"is_featured":15,"company":347,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":350,"processed_country_iso_code_gmaps":352,"processed_home_office":140,"processed_salary_min":353,"processed_salary_max":354,"processed_salary_currency":355,"processed_salary_source":27,"processed_working_hours":356,"processed_employment_types":30,"processed_it_skills":357,"processed_it_skills_labels":358,"processed_job_expertise_skills":364,"processed_job_expertise_skills_labels":365,"max_cpc":100,"actual_cpc":100},95206,"senior-software-engineer-genai-parametric-morgan-stanley-advantage-svcs","Senior Software Engineer (GenAI) - Parametric",{"name":348,"slug":349,"logo_url":5},"Morgan Stanley Advantage Svcs","morgan-stanley-advantage-svcs",[351],"Mumbai",[22],150000,200000,"USD",[29],{"aws":32,"git":32,"docker":143,"python":33,"datadog":143,"pytorch":143,"langchain":32,"rest apis":32,"terraform":143,"llamaindex":32,"tensorflow":143,"prompt engineering":33,"hugging face transformers":143,"ci\u002Fcd (gitlab ci, github actions)":143,"llm apis (openai, azure openai, anthropic)":33},[35,359,360,82,45,48,52,272,273,361,41,154,229,362,363],"REST APIs","LLM APIs (OpenAI, Azure OpenAI, Anthropic)","Hugging Face Transformers","CI\u002FCD (GitLab CI, GitHub Actions)","Datadog",{"fine-tuning":32,"machine learning":33,"model evaluation":33,"vector databases":143,"agentic workflows":32,"agile development":32,"ai development lifecycle":33,"cloud-native development":32,"transformer architectures":33,"microservices architecture":143,"large language models (llms)":33,"natural language processing (nlp)":33,"rag (retrieval-augmented generation)":32},[331,366,367,368,369,93,83,370,79,371,372,373,110],"Natural Language Processing (NLP)","Transformer Architectures","Large Language Models (LLMs)","AI Development Lifecycle","RAG (Retrieval-Augmented Generation)","Cloud-native Development","Microservices Architecture","Agile Development",{"id":375,"slug":376,"title":377,"raw_title":5,"is_featured":15,"company":378,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":381,"processed_country_iso_code_gmaps":382,"processed_home_office":23,"processed_salary_min":383,"processed_salary_max":384,"processed_salary_currency":355,"processed_salary_source":27,"processed_working_hours":385,"processed_employment_types":30,"processed_it_skills":386,"processed_it_skills_labels":387,"processed_job_expertise_skills":389,"processed_job_expertise_skills_labels":390,"max_cpc":100,"actual_cpc":100},99373,"senior-associate-ai-platform-lead-engineer-tiaa-global-capabilities-private-limited","Senior Associate - AI Platform Lead Engineer",{"name":379,"slug":380,"logo_url":5},"TIAA Global Capabilities Private Limited","tiaa-global-capabilities-private-limited",[138],[22],120000,180000,[29],{"aws":33,"mcp":33,"rag":33,"ci\u002Fcd":33,"devops":32,"python":33,"autogen":33,"langchain":33,"langgraph":33,"api design":33,"microservices":33,"machine learning":32},[35,45,48,156,50,201,282,388,168,88,331,304],"API Design",{"fine-tuning slms":33,"llm optimization":33,"ai agent frameworks":33,"cloud infrastructure":33,"multi-agent workflows":33,"model context protocol":33,"enterprise llm solutions":33,"backend system architecture":33,"retrieval-augmented generation":33,"software development life cycle":32},[391,392,393,394,115,395,396,397,398,399],"AI Agent Frameworks","LLM Optimization","Fine-tuning SLMs","Backend System Architecture","Model Context Protocol","Enterprise LLM Solutions","Multi-agent Workflows","Retrieval-Augmented Generation","Software Development Life Cycle",{"id":401,"slug":402,"title":403,"raw_title":5,"is_featured":15,"company":404,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":405,"processed_country_iso_code_gmaps":406,"processed_home_office":140,"processed_salary_min":194,"processed_salary_max":262,"processed_salary_currency":26,"processed_salary_source":27,"processed_working_hours":407,"processed_employment_types":30,"processed_it_skills":408,"processed_it_skills_labels":409,"processed_job_expertise_skills":415,"processed_job_expertise_skills_labels":416,"max_cpc":100,"actual_cpc":100},92330,"quality-assurance-engineer-ai-agentic-applications-avp-f337-deutsche-india-private-limited-pune-branch","Quality Assurance Engineer – AI Agentic Applications, AVP",{"name":135,"slug":136,"logo_url":5},[138],[22],[29],{"sql":32,"java":33,"json":32,"ci\u002Fcd":32,"kafka":32,"ragas":33,"kotlin":33,"openai":32,"python":33,"langfuse":33,"langchain":32,"langgraph":32,"langsmith":33,"rest apis":32,"vertex ai":32,"llamaindex":32},[62,410,35,411,412,413,359,414,36,159,88,48,156,52,317,53],"Kotlin","Langsmith","Langfuse","Ragas","JSON",{"ai agents":33,"embeddings":33,"llm testing":33,"test planning":33,"rag evaluation":33,"reconciliations":32,"test automation":33,"trade lifecycles":32,"vector databases":33,"agentic ai testing":33,"end-to-end testing":33,"functional testing":33,"prompt engineering":33,"regression testing":33,"integration testing":33,"regulatory controls":32,"regulatory reporting":32,"ai evaluation metrics":33,"generative ai testing":33,"tool\u002Ffunction calling":33,"transaction reporting":32,"prompt injection testing":32,"software quality assurance":33,"ai safety and security testing":33,"building automation frameworks":33},[417,418,419,420,421,422,423,424,425,426,427,82,428,84,110,429,430,431,432,433,174,434,435,436,437],"Software Quality Assurance","Test Planning","Functional Testing","Integration Testing","Regression Testing","End-to-End Testing","Test Automation","Building Automation Frameworks","Generative AI Testing","LLM Testing","Agentic AI Testing","RAG Evaluation","AI Agents","Tool\u002FFunction Calling","AI Safety and Security Testing","Prompt Injection Testing","AI Evaluation Metrics","Trade Lifecycles","Transaction Reporting","Reconciliations","Regulatory Controls",{"id":439,"slug":440,"title":441,"raw_title":5,"is_featured":15,"company":442,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":443,"processed_country_iso_code_gmaps":444,"processed_home_office":140,"processed_salary_min":25,"processed_salary_max":445,"processed_salary_currency":26,"processed_salary_source":27,"processed_working_hours":446,"processed_employment_types":30,"processed_it_skills":447,"processed_it_skills_labels":448,"processed_job_expertise_skills":469,"processed_job_expertise_skills_labels":470,"max_cpc":100,"actual_cpc":100},83074,"data-science-and-ai-engineering-lead-vp-f337-deutsche-india-private-limited-pune-branch","Data Science and AI Engineering Lead​, VP",{"name":135,"slug":136,"logo_url":5},[138],[22],8000000,[29],{"adk":33,"gke":33,"sql":32,"java":32,"flask":33,"neo4j":33,"redis":33,"spark":33,"denodo":33,"github":33,"looker":33,"mlflow":33,"python":33,"fastapi":33,"fastmcp":33,"mongodb":33,"pytorch":33,"vs code":33,"bigquery":33,"cloudsql":33,"pinecone":33,"langchain":33,"langgraph":33,"snowflake":33,"databricks":33,"postgresql":33,"tensorflow":33,"claude code":33,"gcp cloudrun":33,"hugging face":33,"scikit-learn":33,"cloud composer":33,"github copilot":33,"google vertexai":33,"jupyter notebook":33,"weights and biases":33},[35,65,449,450,156,451,452,453,454,272,273,455,456,457,458,199,459,460,461,152,153,462,463,464,226,67,230,287,465,466,467,266,36,62,468,71],"Flask","FastMcp","ADK","Google VertexAI","GitHub","VS Code","scikit-learn","MLflow","Weights and Biases","Jupyter Notebook","Langchain","Neo4J","GCP CloudRun","Cloud Composer","CloudSQL","Looker","Redis","Databricks","Denodo","Claude Code",{"deployment":33,"roi analysis":32,"ai governance":33,"api architecture":33,"data engineering":33,"budget management":32,"people management":33,"ai risk management":33,"feature engineering":33,"ai model integration":33,"ai model optimization":33,"data product creation":33,"performance monitoring":33,"testing and validation":33,"research and innovation":33,"ai solution architecture":33,"cross-functional collaboration":33,"cloud infrastructure management":33,"software development lifecycle (sdlc)":33},[471,472,473,474,475,92,476,334,163,477,478,479,480,481,482,483,484,485,486],"AI Solution Architecture","AI Model Integration","AI Model Optimization","API Architecture","Cloud Infrastructure Management","AI Risk Management","Feature Engineering","Data Product Creation","Performance Monitoring","Testing and Validation","Deployment","Research and Innovation","Cross-Functional Collaboration","People Management","Budget Management","ROI Analysis",{"id":488,"slug":489,"title":490,"raw_title":5,"is_featured":15,"company":491,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":492,"processed_country_iso_code_gmaps":493,"processed_home_office":140,"processed_salary_min":194,"processed_salary_max":262,"processed_salary_currency":26,"processed_salary_source":27,"processed_working_hours":494,"processed_employment_types":30,"processed_it_skills":495,"processed_it_skills_labels":496,"processed_job_expertise_skills":519,"processed_job_expertise_skills_labels":520,"max_cpc":100,"actual_cpc":100},88194,"ind-staff-software-engineer-hartford-global-services-private-limited-9","IND Staff Software Engineer",{"name":17,"slug":18,"logo_url":5},[20],[22],[29],{"git":32,"sql":33,"w&b":32,"hnsw":32,"unix":32,"numpy":33,"ragas":32,"mlflow":32,"pandas":33,"python":33,"tabula":32,"camelot":32,"pymupdf":32,"pytorch":32,"trulens":32,"deepeval":32,"layoutlm":32,"pgvector":32,"postgres":32,"ratabase":143,"langchain":32,"langgraph":32,"tesseract":32,"duck creek":143,"llamaindex":32,"opensearch":32,"pdfplumber":32,"tensorflow":32,"apache tika":32,"aws bedrock":32,"scikit-learn":33,"aws sagemaker":32,"google vertex ai":32,"vector databases":32,"azure ai services":32},[35,497,498,455,36,272,273,154,499,55,500,56,501,502,503,504,505,69,506,507,508,509,510,511,512,513,514,515,516,517,48,156,52,456,518],"pandas","NumPy","Unix","AWS SageMaker","Azure AI Services","Duck Creek","Ratabase","vector databases","OpenSearch","Postgres","HNSW","RAGAS","TruLens","DeepEval","PyMuPDF","pdfplumber","Apache Tika","Tesseract","LayoutLM","Camelot","Tabula","W&B",{"nlp":33,"mlops":33,"document ai":32,"agent design":33,"deep learning":33,"generative ai":33,"responsible ai":32,"diffusion models":32,"fine-tuning llms":32,"machine learning":33,"model evaluation":33,"model monitoring":33,"cloud ai platforms":33,"prompt engineering":33,"statistical modeling":33,"regulatory compliance":32,"orchestration frameworks":32,"embedding model selection":32,"synthetic data generation":32,"knowledge base engineering":32,"unstructured data processing":33,"retrieval-augmented generation (rag)":33},[521,331,332,93,522,523,524,198,298,82,525,86,526,527,528,301,529,320,530,531,532,533],"Statistical Modeling","Model Monitoring","Unstructured Data Processing","NLP","Agent Design","Cloud AI Platforms","Regulatory Compliance","Responsible AI","Knowledge Base Engineering","Embedding Model Selection","Orchestration Frameworks","Fine-tuning LLMs","Diffusion Models",{"id":535,"slug":536,"title":537,"raw_title":5,"is_featured":15,"company":538,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":539,"processed_country_iso_code_gmaps":540,"processed_home_office":23,"processed_salary_min":24,"processed_salary_max":25,"processed_salary_currency":26,"processed_salary_source":27,"processed_working_hours":541,"processed_employment_types":30,"processed_it_skills":542,"processed_it_skills_labels":543,"processed_job_expertise_skills":550,"processed_job_expertise_skills_labels":551,"max_cpc":100,"actual_cpc":100},88253,"senior-associate-ai-ml-engineer-tiaa-global-capabilities-private-limited","Senior Associate - AI - ML Engineer",{"name":379,"slug":380,"logo_url":5},[138],[22],[29],{"aws":32,"gcp":32,"azure":32,"faiss":33,"mlflow":32,"python":33,"flowise":32,"pinecone":33,"weaviate":33,"langchain":33,"llamaindex":33,"openai api":33,"hugging face":33,"anthropic api":33,"weights & biases":32,"microsoft copilot studio":32},[35,48,52,544,545,199,67,68,546,45,47,46,456,547,548,549],"OpenAI API","Anthropic API","FAISS","Weights & Biases","Microsoft Copilot Studio","Flowise",{"mlops":32,"statistics":32,"data science":32,"generative ai":33,"multi-modal ai":32,"responsible ai":32,"llm fine-tuning":33,"machine learning":33,"model evaluation":33,"data preprocessing":32,"prompt engineering":33,"ai agent deployment":33,"predictive modeling":32,"observability and monitoring":33,"retrieval-augmented generation (rag)":33},[198,298,82,552,93,553,554,555,528,86,556,557,331,558,559],"LLM Fine-tuning","Observability and Monitoring","AI Agent Deployment","Multi-modal AI","Data Preprocessing","Data Science","Predictive Modeling","Statistics",{"id":561,"slug":562,"title":563,"raw_title":5,"is_featured":15,"company":564,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":568,"processed_country_iso_code_gmaps":570,"processed_home_office":140,"processed_salary_min":571,"processed_salary_max":572,"processed_salary_currency":573,"processed_salary_source":27,"processed_working_hours":574,"processed_employment_types":30,"processed_it_skills":576,"processed_it_skills_labels":577,"processed_job_expertise_skills":582,"processed_job_expertise_skills_labels":583,"max_cpc":100,"actual_cpc":100},81803,"ai-automation-specialist2881-allianz-insurance","AI Automation Specialist_2881",{"name":565,"slug":566,"logo_url":567},"Allianz Insurance","allianz-insurance","https:\u002F\u002Fcdn.phenompeople.com\u002FCareerConnectResources\u002FAISAIPGB\u002Fimages\u002FHeader-1706868786965.svg",[138,569],"Trivandrum",[22],70000,100000,"EUR",[29,575],"PART_TIME",{"sql":32,"faiss":32,"numpy":32,"crewai":33,"pandas":32,"python":33,"autogen":33,"grafana":143,"chromadb":32,"pinecone":32,"power bi":143,"rest api":33,"weaviate":32,"langchain":33,"langgraph":33},[35,36,48,156,50,51,578,67,68,546,70,579,498,580,581],"REST API","Pandas","Grafana","Power BI",{"ci\u002Fcd":32,"devsecops":32,"rag pipelines":33,"data analytics":32,"llm integration":33,"agentic ai development":33,"ai security & guardrails":33,"cybersecurity domain awareness":32},[584,113,78,585,586,587,588,88],"Agentic AI Development","AI Security & Guardrails","Data Analytics","Cybersecurity Domain Awareness","DevSecOps",{"id":590,"slug":591,"title":592,"raw_title":5,"is_featured":15,"company":593,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":594,"processed_country_iso_code_gmaps":595,"processed_home_office":23,"processed_salary_min":353,"processed_salary_max":596,"processed_salary_currency":355,"processed_salary_source":27,"processed_working_hours":597,"processed_employment_types":30,"processed_it_skills":598,"processed_it_skills_labels":599,"processed_job_expertise_skills":605,"processed_job_expertise_skills_labels":606,"max_cpc":100,"actual_cpc":100},85649,"ai-java-lead-engineer-vice-president-software-engineering-morgan-stanley-advantage-svcs","AI Java Lead Engineer _ Vice President _Software Engineering",{"name":348,"slug":349,"logo_url":5},[351],[22],250000,[29],{"jms":33,"rag":143,"sql":33,"java":33,"ci\u002Fcd":33,"kafka":33,"crewai":143,"devops":33,"python":143,"autogen":143,"rabbitmq":33,"langchain":143,"langgraph":143,"rest apis":33,"spring ai":143,"openai api":143,"claude code":143,"spring boot":33,"azure openai":143,"anthropic api":143,"microservices":33,"github copilot":143,"claude agent sdk":143,"vector databases":143},[62,145,168,359,159,600,601,36,88,304,35,544,602,545,71,468,48,156,603,50,51,604,110,201],"JMS","RabbitMQ","Azure OpenAI","Spring AI","Claude Agent SDK",{"react":143,"concurrency":33,"cost management":143,"chain-of-thought":143,"reflection loops":143,"latency management":143,"performance tuning":33,"prompt engineering":143,"tracing agent runs":143,"agentic ai workflows":143,"ai system reliability":143,"eval-driven iteration":143,"multi-agent workflows":143,"tool\u002Ffunction calling":143,"human-in-the-loop gates":143,"hallucination mitigation":143,"production observability":33,"scalability improvements":33,"financial services domain":143,"investment banking domain":143,"distributed systems design":33,"agent-to-agent communication":143,"orchestrator\u002Fsubagent patterns":143,"guardrails for autonomous systems":143},[607,608,242,609,610,611,612,430,613,82,397,614,615,616,617,618,619,620,621,622,623,624,625,626],"Distributed Systems Design","Concurrency","Scalability Improvements","Production Observability","Agentic AI Workflows","Orchestrator\u002FSubagent Patterns","Eval-driven Iteration","Agent-to-agent Communication","Guardrails for Autonomous Systems","AI System Reliability","Hallucination Mitigation","Tracing Agent Runs","Latency Management","Cost Management","ReAct","Chain-of-Thought","Reflection Loops","Human-in-the-loop Gates","Financial Services Domain","Investment Banking Domain",{"id":628,"slug":629,"title":630,"raw_title":5,"is_featured":15,"company":631,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":632,"processed_country_iso_code_gmaps":633,"processed_home_office":23,"processed_salary_min":634,"processed_salary_max":635,"processed_salary_currency":26,"processed_salary_source":27,"processed_working_hours":636,"processed_employment_types":30,"processed_it_skills":637,"processed_it_skills_labels":638,"processed_job_expertise_skills":641,"processed_job_expertise_skills_labels":642,"max_cpc":100,"actual_cpc":100},88180,"ind-director-software-engineering-hartford-global-services-private-limited","IND Director, Software Engineering",{"name":17,"slug":18,"logo_url":5},[20],[22],6000000,10000000,[29],{"aws":33,"gcp":32,"java":33,"devops":32,"python":33,"azure ai":32,"langchain":33,"langgraph":33,"vertex ai":33,"google adk":33,"typescript":33,"aws bedrock":33},[35,60,62,45,46,639,48,156,640,317,56,304],"Azure AI","Google ADK",{"knowledge graphs":33,"agentic ai systems":33,"technical strategy":33,"product development":33,"software engineering":33,"workflow orchestration":33,"ai-augmented integration":33,"cloud-native environments":33,"event-driven architecture":33,"enterprise integration patterns":33},[162,643,644,645,646,300,647,648,649,650],"Enterprise Integration Patterns","Workflow Orchestration","Event-Driven Architecture","Agentic AI Systems","Technical Strategy","Product Development","Cloud-Native Environments","AI-Augmented Integration",{"id":652,"slug":653,"title":654,"raw_title":5,"is_featured":15,"company":655,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":658,"processed_country_iso_code_gmaps":659,"processed_home_office":23,"processed_salary_min":660,"processed_salary_max":661,"processed_salary_currency":26,"processed_salary_source":27,"processed_working_hours":662,"processed_employment_types":30,"processed_it_skills":663,"processed_it_skills_labels":664,"processed_job_expertise_skills":675,"processed_job_expertise_skills_labels":676,"max_cpc":100,"actual_cpc":100},94852,"lead-devops-engineer-refinitiv-india-shared-services-private-limited","Lead Devops Engineer",{"name":656,"slug":657,"logo_url":5},"Refinitiv India Shared Services Private Limited","refinitiv-india-shared-services-private-limited",[191],[22],2000000,3500000,[29],{"aws":32,"gcp":32,"rag":143,"helm":32,"azure":32,"ci\u002Fcd":33,"crewai":143,"docker":33,"python":33,"ansible":33,"autogen":143,"datadog":32,"grafana":32,"jenkins":32,"llm apis":143,"elk stack":143,"gitlab ci":32,"langchain":143,"terraform":33,"kubernetes":33,"prometheus":32,"shell\u002Fbash":33,"azure devops":32,"cloudformation":32,"vector databases":143,"prompt engineering":143,"model context protocol (mcp)":143},[88,229,665,666,667,42,41,47,45,46,668,580,363,35,669,670,43,671,48,50,51,672,673,82,201,110,674],"Helm","CloudFormation","Ansible","Prometheus","Shell\u002FBash","GitLab CI","Azure DevOps","Model Context Protocol (MCP)","LLM APIs","ELK stack",{"devops":33,"agile\u002Fscrum":32,"cloud platforms":32,"containerization":33,"agentic workflows":143,"incident response":33,"network automation":32,"root cause analysis":33,"ai-driven automation":143,"infrastructure as code":33,"monitoring and logging":32,"networking fundamentals":32,"security best practices":32,"site reliability engineering":33},[304,178,677,678,252,249,679,680,681,682,683,684,685,79],"Networking Fundamentals","Incident Response","Containerization","Cloud Platforms","Monitoring and Logging","Security Best Practices","Agile\u002FScrum","Network Automation","AI-driven Automation",{"id":687,"slug":688,"title":689,"raw_title":5,"is_featured":15,"company":690,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":691,"processed_country_iso_code_gmaps":692,"processed_home_office":140,"processed_salary_min":194,"processed_salary_max":262,"processed_salary_currency":26,"processed_salary_source":27,"processed_working_hours":693,"processed_employment_types":30,"processed_it_skills":694,"processed_it_skills_labels":695,"processed_job_expertise_skills":701,"processed_job_expertise_skills_labels":702,"max_cpc":100,"actual_cpc":100},78821,"ind-senior-engineer-data-hartford-global-services-private-limited","IND Senior Engineer, Data",{"name":17,"slug":18,"logo_url":5},[20],[22],[29],{"a2a":33,"aws":33,"mcp":33,"rdf":33,"sql":33,"azure":33,"ci\u002Fcd":33,"neo4j":33,"nosql":33,"spark":33,"aws s3":33,"cypher":33,"docker":33,"python":33,"sparql":33,"aws ec2":33,"mongodb":33,"pytorch":32,"big data":33,"dynamodb":33,"data lake":33,"data mesh":33,"langchain":33,"langgraph":33,"snowflake":33,"aws lambda":33,"kubernetes":33,"tensorflow":32,"aws kinesis":33,"data fabric":33,"apache kafka":33,"document dbs":33,"etl\u002Felt tools":33,"gcp vertex ai":33,"spanner graph":33,"amazon neptune":33,"aws opensearch":33,"graph databases":33,"spark streaming":33,"vector databases":33,"google cloud platform":33},[269,270,271,36,37,266,696,88,268,45,149,47,35,230,293,224,294,41,42,272,273,110,697,698,284,285,274,286,275,287,288,279,699,700,48,156,282,283,278,277,276],"ETL\u002FELT tools","Graph Databases","Document DBs","AWS S3","AWS EC2",{"devops":33,"data lakes":33,"data domains":33,"data lineage":33,"data quality":33,"scaled agile":33,"data products":33,"generative ai":33,"data catalogue":33,"data governance":33,"cloud technology":33,"data engineering":33,"data integration":33,"data warehousing":33,"knowledge graphs":33,"data architecture":33,"semantic modeling":33,"prompt engineering":33,"business intelligence":33,"reliability engineering":33,"synthetic data generation":33,"ai-driven data engineering":33,"insurance domain knowledge":32,"retrieval-augmented generation (rag)":33},[163,291,223,240,292,703,295,296,704,198,298,82,299,300,301,247,243,180,705,706,304,305,303,306],"Data Domains","Cloud Technology","Data Catalogue","AI-driven Data Engineering",{"id":708,"slug":709,"title":710,"raw_title":5,"is_featured":15,"company":711,"raw_hiringOrganization_logo_url":5,"processed_city_gmaps":712,"processed_country_iso_code_gmaps":713,"processed_home_office":23,"processed_salary_min":383,"processed_salary_max":384,"processed_salary_currency":355,"processed_salary_source":27,"processed_working_hours":714,"processed_employment_types":30,"processed_it_skills":715,"processed_it_skills_labels":716,"processed_job_expertise_skills":723,"processed_job_expertise_skills_labels":724,"max_cpc":100,"actual_cpc":730},59769,"lead-data-scientist-ind201-refinitiv-india-shared-services-private-limited-3","Lead Data Scientist",{"name":656,"slug":657,"logo_url":5},[191],[22],[29],{"r":32,"git":32,"nlp":33,"rag":33,"sql":32,"ci\u002Fcd":32,"mlops":33,"llmops":33,"python":33,"ai agents":32,"langchain":32,"llamaindex":32,"web scraping":32,"deep learning":33,"machine learning":33,"vector databases":32,"entity recognition":32,"large language models":33,"synthetic data techniques":32,"cloud platforms (azure\u002Faws)":33},[35,717,36,331,332,524,718,201,86,87,88,154,719,110,48,52,720,429,721,722],"R","Large Language Models","Cloud Platforms (Azure\u002FAWS)","Synthetic Data Techniques","Web Scraping","Entity Recognition",{"statistics":33,"data science":33,"ai governance":32,"product vision":33,"responsible ai":33,"risk frameworks":32,"data engineering":33,"model deployment":33,"model evaluation":33,"investment banking":32,"technical strategy":33,"financial analytics":33,"regulatory compliance":32,"stakeholder engagement":33},[557,559,163,725,726,92,727,527,93,206,728,729,647,528],"Financial Analytics","Investment Banking","Risk Frameworks","Product Vision","Stakeholder Engagement",0.3,{"industry":732,"employment_type":750,"expertise_skills":753,"it_skills":818,"salary_currency":882,"processed_working_hours":887},[733,737,741,744,747],{"key":734,"label":735,"count":736},"insurance","Insurance",11,{"key":738,"label":739,"count":740},"financial services","Financial Services",9,{"key":742,"label":743,"count":33},"financial markets infrastructure","Financial Markets Infrastructure",{"key":745,"label":746,"count":33},"data provider","Data Provider",{"key":748,"label":749,"count":100},"asset management","Asset Management",[751],{"key":30,"label":752,"count":9},"PERMANENT",[754,757,760,763,766,769,771,774,778,781,784,787,789,791,794,797,800,803,806,808,810,812,814,816],{"key":755,"label":82,"slug":755,"count":756},"prompt-engineering",12,{"key":758,"label":93,"slug":758,"count":759},"model-evaluation",10,{"key":761,"label":762,"slug":761,"count":740},"mlops","Mlops",{"key":764,"label":163,"slug":764,"count":765},"data-engineering",8,{"key":767,"label":331,"slug":767,"count":768},"machine-learning",6,{"key":770,"label":79,"slug":770,"count":768},"agentic-workflows",{"key":772,"label":773,"slug":772,"count":768},"generative-ai","Generative Ai",{"key":775,"label":776,"slug":775,"count":777},"devops","Devops",5,{"key":779,"label":780,"slug":779,"count":777},"responsible-ai","Responsible Ai",{"key":782,"label":783,"slug":782,"count":777},"cicd","Ci\u002FCd",{"key":785,"label":786,"slug":785,"count":777},"ai-governance","Ai Governance",{"key":788,"label":301,"slug":788,"count":33},"synthetic-data-generation",{"key":790,"label":84,"slug":790,"count":33},"embeddings",{"key":792,"label":793,"slug":792,"count":33},"infrastructure-as-code","Infrastructure As Code",{"key":795,"label":796,"slug":795,"count":33},"rag-pipelines","Rag Pipelines",{"key":798,"label":799,"slug":798,"count":33},"retrieval-augmented-generation-rag","Retrieval-Augmented Generation (Rag)",{"key":801,"label":802,"slug":801,"count":33},"fine-tuning","Fine-Tuning",{"key":804,"label":805,"slug":804,"count":32},"aiml-engineering","Ai\u002FMl Engineering",{"key":807,"label":85,"slug":807,"count":32},"vector-search",{"key":809,"label":300,"slug":809,"count":32},"knowledge-graphs",{"key":811,"label":243,"slug":811,"count":32},"data-quality",{"key":813,"label":240,"slug":813,"count":32},"data-integration",{"key":815,"label":247,"slug":815,"count":32},"data-governance",{"key":817,"label":115,"slug":817,"count":32},"cloud-infrastructure",[819,821,824,827,831,832,835,838,840,842,844,846,849,852,855,858,862,865,867,869,871,874,877,880],{"key":820,"label":459,"slug":820,"count":9},"langchain",{"key":822,"label":35,"slug":822,"count":823},"python",23,{"key":825,"label":36,"slug":825,"count":826},"sql",15,{"key":828,"label":829,"slug":828,"count":830},"aws","Aws",13,{"key":782,"label":783,"slug":782,"count":830},{"key":833,"label":834,"slug":833,"count":736},"langgraph","Langgraph",{"key":836,"label":837,"slug":836,"count":736},"llamaindex","Llamaindex",{"key":839,"label":41,"slug":839,"count":736},"docker",{"key":841,"label":110,"slug":841,"count":736},"vector-databases",{"key":843,"label":42,"slug":843,"count":759},"kubernetes",{"key":845,"label":62,"slug":845,"count":759},"java",{"key":847,"label":848,"slug":847,"count":759},"gcp","Gcp",{"key":850,"label":851,"slug":850,"count":740},"ms-azure","MS Azure",{"key":853,"label":854,"slug":853,"count":765},"autogen","Autogen",{"key":856,"label":857,"slug":856,"count":765},"crewai","Crewai",{"key":859,"label":860,"slug":859,"count":861},"pytorch","Pytorch",7,{"key":863,"label":864,"slug":863,"count":861},"rag","Rag",{"key":866,"label":322,"slug":866,"count":861},"github-copilot",{"key":868,"label":154,"slug":868,"count":768},"git",{"key":870,"label":229,"slug":870,"count":768},"terraform",{"key":872,"label":873,"slug":872,"count":768},"aws-bedrock","Aws Bedrock",{"key":875,"label":876,"slug":875,"count":768},"fastapi","Fastapi",{"key":878,"label":879,"slug":878,"count":768},"tensorflow","Tensorflow",{"key":881,"label":43,"slug":881,"count":777},"jenkins",[883,885,886],{"key":26,"label":26,"count":884},18,{"key":355,"label":355,"count":777},{"key":573,"label":573,"count":100},[888,889],{"key":29,"label":29,"count":9},{"key":575,"label":575,"count":100},{"total":891,"jobs":892},0,[]]