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Jobs · Information Technology · California

AI Product Engineer - Agentic AI Platforms (Financial Services)

Capgemini · Los Angeles, CA · 3 wk ago
HybridInformation TechnologyFull-time

About the role

Capgemini is at the forefront of Generative AI innovation, helping Financial Services clients industrialize GenAI and Agentic AI platforms at enterprise scale. We are seeking an experienced and innovative AI Product Engineer - Agentic Platforms to join our Financial Services Artificial Intelligence & Business Lines (FS‑ABL) practice.

Responsibilities

  • Partner directly with Financial Services clients to identify, prioritize, and shape Agentic AI use cases across customer operations, underwriting, claims, risk, compliance, finance, and technology.

  • Lead client workshops to define agent personas, responsibilities, autonomy boundaries, human-in-the-loop checkpoints, and escalation logic.

  • Translate evolving business needs into agentic product backlogs, roadmaps, and MVP definitions.

  • Support executive conversations around GenAI platform strategy, operating models, vendor selection, and scale-out approaches.

  • Design and implement multi-agent architectures using modern GenAI tooling, including Planner, executor, reviewer/critic, and supervisor agents.

  • Leverage LangChain and LangGraph for agent orchestration, workflows, and control flow.

  • Apply DSPy and declarative prompt optimization techniques for repeatability, performance tuning, and regression control.

  • Design agent interaction patterns such as hierarchical agents, collaborating agents, and event-driven agent workflows.

  • Define standardized agent contracts, interfaces, and schemas to enable reuse and scale.

  • Own delivery across the full Software Development Lifecycle (SDLC), extending it into a formal Agentic SDLC, including:

    • Agent design specifications and behavior contracts
    • Prompt, policy, and tool versioning
    • Simulation environments and offline evaluation
    • Automated testing of agent flows and guardrails
    • Controlled rollout, telemetry-driven optimization, and continuous learning

  • Build production-grade AI services primarily using Python, integrating:

    • LLM providers such as Anthropic (Claude), OpenAI, and open-source models
    • Retrieval-Augmented Generation (RAG) using vector databases (e.g., Pinecone, FAISS, Milvus, Weaviate)

  • Integrate GenAI agents with client systems via APIs, workflow engines, event streams, and data platforms.

  • Implement CI/CD pipelines for agent code, prompts, and policies.

  • Implement observability including tracing, decision logging, tool usage, and failure analysis.

  • Apply evaluation frameworks for hallucination detection, consistency checks, and fitness scoring.

  • Design feedback loops incorporating human-in-the-loop review and reinforcement.

  • Monitor cost, latency, throughput, and behavioral drift across deployed agents.

  • Design Agentic AI platforms aligned with Financial Services regulatory expectations, including:

    • Auditability and traceability of agent decisions
    • Model and prompt explainability
    • Data privacy and security controls
    • Resilience and fail-safe mechanisms
    • Embed guardrails and policies addressing hallucination risk, bias, unauthorized actions, and escalation failures.

  • Produce documentation supporting risk, compliance, internal audit, and regulator engagement.

  • Provide technical leadership and mentorship to consulting delivery teams.

  • Contribute to internal GenAI accelerators, agent frameworks, and reusable assets.

  • Support RFPs, proposals, and client solution designs with credible GenAI and agentic architectures.

  • Participate in thought leadership on Agentic SDLC, GenAI engineering, and responsible autonomy.

Qualifications

  • Deep expertise in modern GenAI tooling, agentic system design, and enterprise SDLC.

  • Experience working in regulated environments.

  • Familiarity with core insurance platforms like Guidewire, DuckCreek or Majesco.

  • Knowledge of P&C Insurance is a significant plus.

  • Strong understanding of Python and other relevant programming languages.

  • Experience with LLM providers such as Anthropic, OpenAI, and open-source models.

  • Experience with vector databases like Pinecone, FAISS, Milvus, and Weaviate.

  • Experience with DSPy and declarative prompt optimization techniques.

  • Experience with LangChain and LangGraph for agent orchestration, workflows, and control flow.

  • Experience with automated testing and CI/CD pipelines.

  • Experience with observability tools and techniques.

  • Experience with financial services regulations and compliance requirements.

Skills

  • Strong problem-solving and analytical skills.

  • Excellent communication and collaboration skills.

  • Ability to work independently and as part of a team.

  • Experience with Agile methodologies and project management tools.

  • Experience with cloud platforms and infrastructure.

  • Experience with data science and machine learning tools.

  • Experience with generative AI and natural language processing technologies.

  • Experience with software development best practices and standards.

  • Experience with financial services and regulatory compliance.

Benefits

This position comes with competitive compensation and benefits package: Competitive salary and performance-based bonusesComprehensive benefits packageCareer development and training opportunitiesFlexible work arrangements (remote and/or office-based)Dynamic and inclusive work culture within a globally known groupPrivate Health InsuranceRetirement BenefitsPaid Time OffTraining & Development

Pay

Competitive salary and performance-based bonuses

Schedule

Flexible work arrangements (remote and/or office-based)

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