[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-devsecops-ai-engineer-fmd-allianz-insurance-de-de":3},{"id":4,"slug":5,"title":6,"description":7,"company":8,"is_featured":12,"featured_until":7,"is_active":13,"deactivated_at":7,"is_enriched":13,"processed_job_posting_json":14,"processed_latitude":88,"processed_longitude":89,"processed_employment_types":90,"processed_working_hours":91,"processed_working_hours_labels":93,"processed_home_office":94,"processed_salary_min":85,"processed_salary_max":86,"processed_salary_currency":82,"processed_salary_source":95,"processed_benefits":96,"processed_benefits_labels":106,"processed_industry":107,"processed_skills":7,"processed_job_location":108,"processed_full_address_gmaps":110,"processed_street_gmaps":111,"processed_city_gmaps":112,"processed_postal_code_gmaps":113,"processed_country_gmaps":115,"processed_country_iso_code_gmaps":117,"full_description":17,"formatted_description":118,"processed_employment_types_labels":35,"processed_home_office_labels":33,"processed_industry_labels":37,"processed_it_skills":119,"processed_it_skills_labels":122,"processed_soft_skills":123,"processed_soft_skills_labels":124,"processed_job_expertise_skills":125,"processed_job_expertise_skills_labels":126,"processed_language_requirements":127,"processed_total_experience_years":121,"processed_professional_field":134,"processed_professional_field_labels":137,"processed_leadership_role":12,"processed_date_posted":20,"raw_job_url":138,"apply_url":7,"raw_hiringOrganization_logo_url":7,"translations":7,"canonical_industry_key":107,"canonical_industry_label":37,"max_cpc":139,"actual_cpc":7},71400,"devsecops-ai-engineer-fmd-allianz-insurance","DevSecOps AI Engineer (f\u002Fm\u002Fd)",null,{"name":9,"slug":10,"logo_url":11},"Allianz Insurance","allianz-insurance","https:\u002F\u002Fcdn.phenompeople.com\u002FCareerConnectResources\u002FAISAIPGB\u002Fimages\u002FHeader-1706868786965.svg",false,true,{"@context":15,"@type":16,"title":6,"description":17,"hiringOrganization":18,"datePosted":20,"validThrough":21,"jobLocation":22,"jobLocationType":33,"employmentType":34,"industry":36,"skills":38,"baseSalary":80},"https:\u002F\u002Fschema.org\u002F","JobPosting","\u003Cp>\u003Cstrong> \u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>This permanent role is part of the Development Transformation & Technology (DTT) team at AllianzGI. DTT enables secure, resilient, and scalable technology delivery across the organization by building and evolving the Internal Developer Platform (IDP) and the surrounding SDLC toolchain.\u003C\u002Fp>\u003Cp> \u003C\u002Fp>\u003Cp>Role intent: This position blends an AI Engineer profile with SDLC platform engineering. You will design and build dedicated, reusable solutions that embed AI into the SDLC (AI4SDLC) and ensure AI\u002FGenAI-enabled applications are built securely and compliantly by default (SDLC4AI). These solutions are horizontal capabilities (platform building blocks, services, templates, automations, agents) that scale across teams and form the tool foundation for other technical platforms to base their solutions upon.\u003C\u002Fp>\u003Cp> \u003C\u002Fp>\u003Cp>Demarcation to AI CoE: AllianzGI has established an AI Center of Enablement (AI CoE) to accelerate AI transformation across AllianzGI. The AI CoE focuses on use-case technologies and delivery, complementing DTT. This role (in DTT) focuses on the overarching technology foundation for development: standardized SDLC\u002FDevSecOps\u002FIDP integration, guardrails, controls, and reusable components that make AI delivery scalable and secure across the organization.\u003C\u002Fp>\u003Cp> \u003C\u002Fp>\u003Cp>DTT’s roadmap explicitly includes initiatives such as SDLC4AI, an SDLC AI Assistant, and expanding AI-enabled SDLC toolchain capabilities (coding agents, orchestration, evidence automation, KPI dashboards).\u003C\u002Fp>\u003Cp> \u003C\u002Fp>\u003Cp>Scope \u002F impact: This role creates tangible, reusable AI capabilities that directly support DTO’s AI strategy by making AI-enabled delivery scalable, secure, and low-friction; while keeping governance and compliance embedded by default.\u003C\u002Fp>\u003Cp> \u003C\u002Fp>\u003Cp>\u003Cstrong>We value strong engineering fundamentals, sound judgment, and the ability to grow durable platform capabilities over rigid alignment to any single background or experience profile.\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp> \u003C\u002Fp>\u003Cp>\u003Cstrong>This position will be based in Frankfurt\u003C\u002Fstrong>.\u003C\u002Fp>\u003Cp> \u003C\u002Fp>\u003Cp>\u003Cstrong>What you will do\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cstrong> \u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>Build AI4SDLC solutions (AI to accelerate software delivery):\u003C\u002Fp>\u003Cul>\u003Cli>Build and productize “horizontal” AI capabilities that integrate with SDLC tools (e.g., GitHub, CI\u002FCD, artifact repositories, Jira\u002FITSM, observability) to reduce friction and automate repeatable work\u003C\u002Fli>\u003Cli>Implement and operationalize SDLC AI Agents (and related agentic patterns) to support developers with setup\u002Ftesting\u002Fmaintenance and workflow automation across the toolchain\u003C\u002Fli>\u003Cli>Build AI-assisted patterns for security remediation and quality gates (e.g., support patterns for remediating security findings; AI-enabled guardrails in pipelines)\u003C\u002Fli>\u003C\u002Ful>\u003Cp> \u003C\u002Fp>\u003Cp>Build SDLC4AI solutions (secure & compliant lifecycle for AI systems):\u003C\u002Fp>\u003Cul>\u003Cli>Implement SDLC4AI building blocks that embed AI lifecycle, governance, compliance, and operational controls into standard delivery patterns (design→build→test→release→run→decom)\u003C\u002Fli>\u003Cli>Ensure alignment with AllianzGI’s Responsible AI lifecycle process and related governance expectations (phased lifecycle, testing\u002Fgo-live\u002Frun\u002Fdecommissioning considerations)\u003C\u002Fli>\u003C\u002Ful>\u003Cp> \u003C\u002Fp>\u003Cp>Engineering & platform integration (enterprise-grade):\u003C\u002Fp>\u003Cul>\u003Cli>Build secure, reusable services\u002Fcomponents (APIs, pipelines, templates, policy packs) that can be consumed by multiple teams and scaled through the IDP\u003C\u002Fli>\u003Cli>Implement LLM\u002Fagent integration patterns that are secure by design (identity\u002Fentitlement-aware execution; auditability; restricted execution environments where required)\u003C\u002Fli>\u003Cli>Engineer reliability and operational readiness: telemetry, monitoring, incident handling hooks, runbooks, and safe rollout strategies for AI-enabled SDLC components\u003C\u002Fli>\u003C\u002Ful>\u003Cp> \u003C\u002Fp>\u003Cp>Cross-team enablement & delivery partnership:\u003C\u002Fp>\u003Cul>\u003Cli>Partner with the AI CoE to ensure use-case delivery can reliably consume DTT’s SDLC foundations and can be deployed\u002Foperated consistently through the enterprise toolchain\u003C\u002Fli>\u003Cli>Contribute to adoption enablement (demos, guidance, blueprints, best practices) to help teams unlock value from AI4SDLC safely and efficiently\u003C\u002Fli>\u003Cli>Become part of the AI Engineering Community of Practise (CoP)\u003C\u002Fli>\u003C\u002Ful>\u003Cp>\u003Cstrong> \u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cstrong>What you bring \u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cstrong> \u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>Required:\u003C\u002Fp>\u003Cul>\u003Cli>3+ years of professional software engineering experience with demonstrated delivery of production-grade services and automation (platform\u002Ftooling context strongly preferred)\u003C\u002Fli>\u003Cli>Candidates must provide objective, verifiable evidence of recent hands-on experience (i.e., GitHub repositories, demonstrable project artifacts)\u003C\u002Fli>\u003Cli>Strong hands-on engineering experience in at least one of the following: Python, TypeScript\u002FJavaScript, Java, C#; plus API design and integration patterns (REST\u002Fevents)\u003C\u002Fli>\u003Cli>Practical experience implementing AI\u002FLLM-enabled solutions in enterprise contexts (e.g., orchestration, agentic workflows, prompt\u002Ftool integration, retrieval patterns) and making them production-ready (testing, observability, rollout)\u003C\u002Fli>\u003Cli>Experience integrating with SDLC ecosystems (Git workflows, CI\u002FCD, quality gates, artifact management, issue\u002Fwork tracking, observability) and automating workflows\u003C\u002Fli>\u003Cli>Strong engineering mindset for security-by-design and compliance-by-default; ability to translate governance requirements into implementable technical controls across pipelines\u002Fservices\u003C\u002Fli>\u003Cli>Ability to create reusable building blocks (templates, libraries, services, pipelines) and drive adoption through documentation, enablement, and pragmatic standards\u003C\u002Fli>\u003Cli>Excellent communication and stakeholder collaboration skills across platform teams and use-case delivery teams (incl. AI CoE)\u003C\u002Fli>\u003Cli>Fluency in English both written and spoken; additional languages are a plus\u003C\u002Fli>\u003C\u002Ful>\u003Cp> \u003C\u002Fp>\u003Cp>Preferred:\u003C\u002Fp>\u003Cul>\u003Cli>Experience with agentic AI patterns for developer productivity (coding agents, workflow agents, copilots) and integrating them safely into SDLC workflows\u003C\u002Fli>\u003Cli>Experience with platform engineering \u002F IDP concepts (“golden paths”, self-service, workflow orchestration, standardization)\u003C\u002Fli>\u003Cli>Familiarity with Responsible AI governance expectations and lifecycle processes; ability to implement guardrails and evidence automation\u003C\u002Fli>\u003Cli>Cloud\u002Fsecurity certifications (examples): Azure AI Engineer, Azure Security Engineer, CCSK, CKA\u002FCKS, Terraform Associate, plus security\u002FDevOps certifications where applicable\u003C\u002Fli>\u003C\u002Ful>\u003Cp> \u003C\u002Fp>\u003Cp>\u003Cstrong>What we offer\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp> \u003C\u002Fp>\u003Cul>\u003Cli>We empower our employees by ensuring flexible work arrangements that maintain a balance between performance, productivity, career development and personal priorities (e.g., hybrid model\u002F flexible working hours)\u003C\u002Fli>\u003Cli>Securing your future: Access to company pension\u002Fsavings plans\u003C\u002Fli>\u003Cli>Family support (relocation\u002F childcare facilities)\u003C\u002Fli>\u003Cli>Company share purchasing plan\u003C\u002Fli>\u003Cli>Mental health and wellbeing programs\u003C\u002Fli>\u003Cli>Mobility solutions (Jobrad bike leasing, subvention Jobticket)\u003C\u002Fli>\u003Cli>Career opportunities within the entire Allianz Group\u003C\u002Fli>\u003Cli>Self-guided learning & development\u003C\u002Fli>\u003Cli>Volunteering time\u003C\u002Fli>\u003Cli>… and so much more!\u003C\u002Fli>\u003C\u002Ful>\u003Cp> \u003C\u002Fp>",{"@type":19,"name":9},"Organization","2026-09-16","2027-09-16",[23],{"@type":24,"address":25,"geo":29},"Place",{"@type":26,"addressLocality":27,"addressCountry":28},"PostalAddress","Frankfurt","DE",{"@type":30,"latitude":31,"longitude":32},"GeoCoordinates",50.12696,8.66796,"HYBRID",[35],"PERMANENT",[37],"Insurance",[39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79],"Python","TypeScript","JavaScript","Java","C#","API design","REST","Event-driven architecture","GitHub","CI\u002FCD","Artifact repositories","Jira","ITSM","Observability tools","LLM integration","Agentic workflows","Prompt engineering","Retrieval patterns","Cloud platforms (Azure)","Terraform","Kubernetes","Communication","Stakeholder collaboration","Engineering mindset","Ability to drive adoption","Sound judgment","Software engineering","Platform engineering","DevSecOps","AI\u002FLLM solution implementation","SDLC integration","Security-by-design","Compliance-by-default","Responsible AI governance","Internal Developer Platform (IDP) concepts","Workflow automation","Reusable component development","Telemetry and monitoring","Incident handling","Runbook creation","Safe rollout strategies",{"@type":81,"currency":82,"value":83},"MonetaryAmount","EUR",{"@type":84,"minValue":85,"maxValue":86,"unitText":87},"QuantitativeValue",70000,95000,"YEAR",[31],[32],"permanent",[92],"FULL_TIME",[92],"hybrid","estimated",[97,98,99,100,101,102,103,104,105],"Flexible work arrangements (hybrid model, flexible working hours)","Company pension\u002Fsavings plans","Family support (relocation\u002Fchildcare facilities)","Company share purchasing plan","Mental health and wellbeing programs","Mobility solutions (Jobrad bike leasing, subsidized Jobticket)","Career opportunities within the entire Allianz Group","Self-guided learning & development","Volunteering time",[97,98,99,100,101,102,103,104,105],"insurance",[109],"allianz, 60323, frankfurt, germany",[],[],[27],[114],"60323",[116],"Germany",[28],"This permanent role is part of the Development Transformation & Technology (DTT) team at AllianzGI. DTT enables secure, resilient, and scalable technology delivery across the organization by building and evolving the Internal Developer Platform (IDP) and the surrounding SDLC toolchain.\n\nRole intent: This position blends an AI Engineer profile with SDLC platform engineering. You will design and build dedicated, reusable solutions that embed AI into the SDLC (AI4SDLC) and ensure AI\u002FGenAI-enabled applications are built securely and compliantly by default (SDLC4AI). These solutions are horizontal capabilities (platform building blocks, services, templates, automations, agents) that scale across teams and form the tool foundation for other technical platforms to base their solutions upon.\n\nDemarcation to AI CoE: AllianzGI has established an AI Center of Enablement (AI CoE) to accelerate AI transformation across AllianzGI. The AI CoE focuses on use-case technologies and delivery, complementing DTT. This role (in DTT) focuses on the overarching technology foundation for development: standardized SDLC\u002FDevSecOps\u002FIDP integration, guardrails, controls, and reusable components that make AI delivery scalable and secure across the organization.\n\nDTT’s roadmap explicitly includes initiatives such as SDLC4AI, an SDLC AI Assistant, and expanding AI-enabled SDLC toolchain capabilities (coding agents, orchestration, evidence automation, KPI dashboards).\n\nScope \u002F impact: This role creates tangible, reusable AI capabilities that directly support DTO’s AI strategy by making AI-enabled delivery scalable, secure, and low-friction; while keeping governance and compliance embedded by default.\n\n**We value strong engineering fundamentals, sound judgment, and the ability to grow durable platform capabilities over rigid alignment to any single background or experience profile.**\n\n**This position will be based in Frankfurt**.\n\n## What you will do\n\nBuild AI4SDLC solutions (AI to accelerate software delivery):\n\n- Build and productize “horizontal” AI capabilities that integrate with SDLC tools (e.g., GitHub, CI\u002FCD, artifact repositories, Jira\u002FITSM, observability) to reduce friction and automate repeatable work\n- Implement and operationalize SDLC AI Agents (and related agentic patterns) to support developers with setup\u002Ftesting\u002Fmaintenance and workflow automation across the toolchain\n- Build AI-assisted patterns for security remediation and quality gates (e.g., support patterns for remediating security findings; AI-enabled guardrails in pipelines)\n\nBuild SDLC4AI solutions (secure & compliant lifecycle for AI systems):\n\n- Implement SDLC4AI building blocks that embed AI lifecycle, governance, compliance, and operational controls into standard delivery patterns (design→build→test→release→run→decom)\n- Ensure alignment with AllianzGI’s Responsible AI lifecycle process and related governance expectations (phased lifecycle, testing\u002Fgo-live\u002Frun\u002Fdecommissioning considerations)\n\nEngineering & platform integration (enterprise-grade):\n\n- Build secure, reusable services\u002Fcomponents (APIs, pipelines, templates, policy packs) that can be consumed by multiple teams and scaled through the IDP\n- Implement LLM\u002Fagent integration patterns that are secure by design (identity\u002Fentitlement-aware execution; auditability; restricted execution environments where required)\n- Engineer reliability and operational readiness: telemetry, monitoring, incident handling hooks, runbooks, and safe rollout strategies for AI-enabled SDLC components\n\nCross-team enablement & delivery partnership:\n\n- Partner with the AI CoE to ensure use-case delivery can reliably consume DTT’s SDLC foundations and can be deployed\u002Foperated consistently through the enterprise toolchain\n- Contribute to adoption enablement (demos, guidance, blueprints, best practices) to help teams unlock value from AI4SDLC safely and efficiently\n- Become part of the AI Engineering Community of Practise (CoP)\n\n## What you bring\n\nRequired:\n\n- 3+ years of professional software engineering experience with demonstrated delivery of production-grade services and automation (platform\u002Ftooling context strongly preferred)\n- Candidates must provide objective, verifiable evidence of recent hands-on experience (i.e., GitHub repositories, demonstrable project artifacts)\n- Strong hands-on engineering experience in at least one of the following: Python, TypeScript\u002FJavaScript, Java, C#; plus API design and integration patterns (REST\u002Fevents)\n- Practical experience implementing AI\u002FLLM-enabled solutions in enterprise contexts (e.g., orchestration, agentic workflows, prompt\u002Ftool integration, retrieval patterns) and making them production-ready (testing, observability, rollout)\n- Experience integrating with SDLC ecosystems (Git workflows, CI\u002FCD, quality gates, artifact management, issue\u002Fwork tracking, observability) and automating workflows\n- Strong engineering mindset for security-by-design and compliance-by-default; ability to translate governance requirements into implementable technical controls across pipelines\u002Fservices\n- Ability to create reusable building blocks (templates, libraries, services, pipelines) and drive adoption through documentation, enablement, and pragmatic standards\n- Excellent communication and stakeholder collaboration skills across platform teams and use-case delivery teams (incl. AI CoE)\n- Fluency in English both written and spoken; additional languages are a plus\n\nPreferred:\n\n- Experience with agentic AI patterns for developer productivity (coding agents, workflow agents, copilots) and integrating them safely into SDLC workflows\n- Experience with platform engineering \u002F IDP concepts (“golden paths”, self-service, workflow orchestration, standardization)\n- Familiarity with Responsible AI governance expectations and lifecycle processes; ability to implement guardrails and evidence automation\n- Cloud\u002Fsecurity certifications (examples): Azure AI Engineer, Azure Security Engineer, CCSK, CKA\u002FCKS, Terraform Associate, plus security\u002FDevOps certifications where applicable\n\n## What we offer\n\n- We empower our employees by ensuring flexible work arrangements that maintain a balance between performance, productivity, career development and personal priorities (e.g., hybrid model\u002F flexible working hours)\n- Securing your future: Access to company pension\u002Fsavings plans\n- Family support (relocation\u002F childcare facilities)\n- Company share purchasing plan\n- Mental health and wellbeing programs\n- Mobility solutions (Jobrad bike leasing, subvention Jobticket)\n- Career opportunities within the entire Allianz Group\n- Self-guided learning & development\n- Volunteering time\n- … and so much more!",{"c#":120,"itsm":121,"java":120,"jira":121,"rest":120,"ci\u002Fcd":120,"github":120,"python":120,"terraform":121,"api design":120,"javascript":120,"kubernetes":121,"typescript":120,"llm integration":120,"agentic workflows":120,"prompt engineering":121,"retrieval patterns":121,"observability tools":121,"artifact repositories":121,"cloud platforms (azure)":121,"event-driven architecture":121},4,3,[39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59],{"communication":120,"stakeholder collaboration":120,"engineering mindset":120,"ability to drive adoption":120,"sound judgment":120},[60,61,62,63,64],{"devsecops":120,"runbook creation":121,"sdlc integration":120,"incident handling":121,"security-by-design":120,"workflow automation":120,"platform engineering":120,"software engineering":120,"compliance-by-default":120,"safe rollout strategies":121,"telemetry and monitoring":121,"responsible ai governance":121,"ai\u002Fllm solution implementation":120,"reusable component development":120,"internal developer platform (idp) concepts":121},[65,66,67,68,69,70,71,72,73,74,75,76,77,78,79],{"detected_language_jobad":128,"required":129},"en",[130],[131],{"language":132,"level":133},"ENGLISH","C1",[135,136],"Software and Applications Development and Analysis","Database and Network Professionals",[135,136],"https:\u002F\u002Fcareers.allianz.com\u002Fglobal\u002Fen\u002Fjob\u002F98192\u002Fdevsecops-ai-engineer-f-m-d",1]