Generative AI Lead

The GenAI Lead defines the vision, strategy, and roadmap for coding agent capabilities across the Stellantis software engineering ecosystem. This role oversees platforms and agentic development capabilities designed to improve developer productivity, strengthen software quality, and increase overall engineering effectiveness.

• Strategy and roadmap
  • Define and communicate a clear vision, strategy, and multi-year roadmap for coding agent capabilities aligned with Stellantis software engineering, AI, and digital transformation priorities.
  • Set platform direction and prioritize investments based on business value, developer productivity, software quality, scalability, risk, and enterprise needs.
• Platform delivery and adoption
  • Lead the evaluation, rollout, and continuous improvement of solutions such as Git Hub Copilot, Claude Code, Codex, Open Code, and related agentic coding capabilities.
  • Translate strategic priorities into clear epics, target outcomes, adoption plans, and delivery roadmaps for internal teams and external partners.
  • Establish the operating model for coding agents, including onboarding, enablement, usage policies, support, and collaboration across engineering communities.
• Team and partner leadership
  • Build, grow, and organize the team and ecosystem required to support the coding agent strategy, including internal capabilities, ways of working, and regional coordination.
  • Coordinate external suppliers and strategic partners to ensure delivery quality, cost control, alignment with Stellantis standards, and execution against roadmap commitments.
• Performance and governance
  • Define and track KPIs such as adoption, active usage, productivity uplift, cycle-time reduction, code quality improvement, and measurable engineering and business impact.
  • Work closely with engineering leaders, enterprise architecture, cybersecurity, legal, procurement, finance, and operations teams to ensure consistent execution and governance.
  • Ensure coding agent capabilities are deployed responsibly, with guardrails for security, compliance, privacy, intellectual property protection, and enterprise risk management.

• Bachelor’s degree in Engineering, Computer Science, or a related field
• Minimum 8 years of software engineering experience
• Strong programming skills:
  • Python (AI/automation)
  • C/C++ (embedded systems preferred)
  • Java/Type Script (enterprise systems)
• Experience with cloud platforms

• Hands‑on experience with:
  • LLMs (OpenAI, Azure OpenAI, etc.)
  • Prompt engineering and RAG architectures
• Experience building:
  • AI assistants, copilots, or agent‑based systems
• Familiarity with:
  • Lang Chain, Semantic Kernel, or similar frameworks
  • Vector databases and retrieval systems

• Experience with:
  • Embedded software or vehicle systems (ECU, AUTOSAR, CAN)
  • Software‑defined vehicle (SDV) architectures
• Understanding of:
  • Automotive development lifecycle (ASPICE, V‑model)
  • Validation and testing processes for vehicle software

• Experience with:
  • CI/CD pipelines for large‑scale engineering systems
  • Containerization (Docker, Kubernetes)
• Strong system design and distributed architecture skills

• Proven experience leading engineering teams (2+ years)
• Experience working across:
  • Product engineering
  • Manufacturing
  • IT / enterprise systems

• Experience in automotive OEMs or Tier 1 suppliers
• Knowledge of:
  • ROS (Robot Operating System) for robotics/manufacturing use cases
  • Edge computing and IoT systems
• Experience in:
  • Developer productivity platforms
  • AI governance in regulated environments