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.
Role Accountabilities:
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 GitHub Copilot, Claude Code, Codex, OpenCode, 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.
Basic Qualifications:
Technical Expertise:
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/TypeScript (enterprise systems)
Experience with cloud platforms
AI / GenAI Skills:
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:
LangChain, Semantic Kernel, or similar frameworks
Vector databases and retrieval systems
Automotive Domain Experience (Highly Preferred):
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
Systems & DevOps:
Experience with:
CI/CD pipelines for large-scale engineering systems
Containerization (Docker, Kubernetes)
Strong system design and distributed architecture skills
Leadership:
Proven experience leading engineering teams (2+ years)
Experience working across:
Product engineering
Manufacturing
IT / enterprise systems
Preferred Qualifications:
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