Senior AI / ML OPS Engineer

Job description

**Job Title:** Senior AI / ML OPS Engineer -- Agentic AI for IT Production **Department:** IPS- CARDIF **About Business Line/Function** BNP Paribas CARDIF is the insurance subsidiary of BNP Paribas. We are a worldwide leader of the Credit Protection Insurance market with strong positions in savings and protection insurance in more than 30 countries in Europe, Asia and Latin America. The Infrastructure \& Production function is responsible for ensuring stability, performance, security and availability of application services throughout their lifecycle. Operating in a continuously evolving technical environment, the team works closely with development and business stakeholders within an Agile and DevOps framework, while driving operational excellence and continuous improvement. **Position Purpose** The Senior AI / ML OPS Engineer plays a key technical role in the design, industrialization and operation of agentic AI systems for IT Production. This position bridges advanced AI engineering with production‑grade operational requirements, ensuring that AI‑driven automation is secure, observable, reliable and scalable in a real RUN environment. **Context \& Objective Of This Position** Within a highly critical production environment, the objective is to: * Design and evolve agentic AI production agents capable of reasoning on operational signals * Integrate AI agents with production platforms, observability stacks and automation tools * Ensure production readiness, control, auditability and security of AI‑driven actions * Support the progressive industrialization of AIOps use cases **Responsibilities** Direct Responsibilities: * Design, develop and operate agentic AI systems using frameworks such as LangChain / LangGraph (or equivalents) * Implement reasoning, planning, decision and orchestration logic for production automation * Integrate AI agents into CI/CD pipelines and ML/AI OPS processes * Connect AI agents to observability systems (Dynatrace, logs, metrics, traces) * Define safeguards, approval mechanisms, rollback and human‑in‑the‑loop controls * Ensure compliance with security, reliability and operational governance standards **Contributing Responsibilities** * Collaborate with OPS, SRE, APS, Architects and AI experts in cross‑functional squads * Participate in testing, validation and gradual rollout of AI‑driven use cases * Contribute to post‑incident analysis, continuous improvement and reliability engineering * Produce and maintain technical and operational documentation compatible with RUN expectations **Technical \& Behavioral Competencies** Technical Skills * Advanced Python development and API‑based system integration * Experience with agentic AI frameworks (LangChain, LangGraph, LangSmith or similar) * Strong understanding of production constraints: availability, performance, security, auditability * AI / ML OPS concepts, CI/CD, lifecycle management * Observability: logs, metrics, traces, alerting (Dynatrace, Elastic, etc.) Production \& OPS Skills * Strong background in IT Production / Operations / SRE * Incident, problem and change management (ITIL mindset) * Secure‑by‑design automation and controlled execution of production actions **Specific Qualifications** * 7--12 years of professional experience in IT Production, Operations, SRE, DevOps or Platform Engineering, including senior responsibility scopes * Proven experience designing or operating automation systems in production environments * Solid hands‑on expertise in Python development and integration with APIs, scripts, workflows or schedulers * Practical experience with AI or ML systems used in operational or production contexts (AIOps, decision engines, automation logic) * Exposure to agent‑based or AI‑driven frameworks (e.g. LangChain, LangGraph, LangSmith or equivalent conceptual frameworks) is highly valued * Strong understanding of production governance, security, reliability and auditability constraints * Experience working in international, multi‑site environments (collaboration with Europe / Asia / LATAM teams) This role targets senior profiles capable of acting as a technical backbone for AI‑driven IT Production initiatives within ISPL. **Skills Referential (Required Knowledge, Skills And Abilities)** **Technical \& Engineering Skills** * Advanced Python programming and system integration capabilities * Strong experience with API‑based architectures and service integration * Ability to design and implement automation workflows suitable for production execution * Solid understanding of DevOps and CI/CD pipelines, including lifecycle management * Familiarity with production platforms, cloud‑based environments and modern OPS toolchains **AI \& Agentic Systems Knowledge** * Strong understanding of agentic AI concepts, including: * Decision‑making logic * Reasoning and planning flows * Orchestration of actions * Experience building or integrating AI agents into real production contexts, not limited to experimentation * Ability to connect AI agents with observability and monitoring systems (metrics, logs, traces) * Knowledge of safeguards, approval mechanisms, rollback strategies and human‑in‑the‑loop patterns for AI‑driven automation **Production \& OPS Abilities** * Deep knowledge of IT Production constraints: * Availability and resiliency * Performance and capacity * Security, compliance and audit requirements * Strong experience with incident, problem and change management * Ability to design automation that improves reliability without increasing operational risk * Capability to translate operational reality (runbooks, procedures, constraints) into AI‑compatible logic and workflows **Behavioral Skills** * Strong ownership and accountability for production‑grade deliverables * Ability to operate with high autonomy in complex and evolving environments * Structured and methodical approach to problem solving and system design * Capa