Description
We are the movers of the world and the makers of the future. At Ford, we're all a part of something bigger than ourselves. Are you ready to change the way the world moves?
Join us and challenge your IT expertise and analytical skills to help create vehicles that are as smart as you are.
The VSSE- Ecosystem of AI Tools (VSSE-EAT) is at the forefront of Ford's mission to integrate artificial intelligence into the heart of vehicle engineering. We are looking for a Technical Lead to lead a multidisciplinary team in transforming a fragmented collection of 0 to 1 stage AI projects into a robust, interconnected, and enterprise-scale ecosystem to drive quantified business value.
In this role, you will move beyond managing individual features. You will be the visionary architect of a platform that allows AI tools to collaborate using advanced frameworks such as Agent to Agent(A2A) or Model Context Protocol (MCP).
Responsibilities
Scaling & Standardization
- From POC to Production: Lead the re-architecting of tools currently in Discovery or POC stages to ensure they are compliant with Ford standards and can scale to support 1000s of global users.
- Robust Frameworks: Collaborate with your squad of Full-stack, Data and DevOps engineers to build an integrated and extensible framework that is both robust and efficient.
- Governance: Establish the 'rules of the road' for AI tools within the ecosystem, ensuring they are secure, compliant, and maintainable.
Ecosystem Orchestration & MCP Leadership
- Multi-Agentic Strategy: Design the framework for a multi-agentic architecture where specialized agents (focused on hardware, electrical, or software) can collaborate seamlessly.
- MCP at Ford: Take the lead in implementing the enterprise standard for Model Context Protocol (MCP) in the VSSE ecosystem. You will define how different AI agents and tools share context and data to solve complex automotive problems in a secure and scalable way.
- Low-Code Empowerment: Drive the product roadmap for an Agent Builder that allows non-technical business customers to create and deploy AI agents, while maintaining the technical depth required for engineering teams.
Cross-Functional Leadership & Metrics
- Squad Leadership: Lead a dedicated team of Data Scientists, Product Designers, and Developers. You are the 'glue' that connects user experience (UX) with deep data science and backend stability.
- Business Collaboration: Work closely with business customers to understand Ford-specific data (Hardware, Electrical, Software) to ensure data integrity and alignment.
Qualifications
- Bachelors degree in computer science, Engineering, or a related technical field, Masters degree preferred.
- 7+ years in software development
- 2+ years focused on Generative AI
- 3+ years of experience defining product vision, strategy, product roadmaps and building and managing backlogs
- 2+ years working with Agile software methodologies (Scrum, eXtreme Programming, Kanban)
- AI/ML Fundamental Literacy: Deep understanding of the LLM lifecycle, including fine-tuning, Retrieval-Augmented Generation (RAG), and the difference between probabilistic and deterministic outputs.
- Software Engineering Foundation: A background in professional software development (e.g., Python, Java, or C++). You must be able to discuss system architecture, API design, and latency trade-offs with your engineers.
- Architecting for Scale: Proven experience taking a software product from a local 'lab' environment to a production environment supporting hundreds of concurrent users (knowledge of Kubernetes, cloud scaling, and load balancing).
- Protocol & Framework Knowledge: Ability to quickly master and implement emerging protocols like Model Context Protocol (MCP) and multi-agent orchestration frameworks (e.g., LangChain, AutoGen, or CrewAI).
- Data Systems: Proficiency in navigating complex data environments, specifically how to integrate AI tools with enterprise data lakes while maintaining governance.
- Lifecycle Management: Experience managing the 'Maturity Pipeline' - moving products from Discovery/POC through Beta to a hardened Production state.
- Platform Thinking: Ability to move beyond 'single-feature' thinking to build an extensible ecosystem where tools share context and interact via a unified framework.
- Metric-Driven Leadership: A track record of optimizing Time to Market (TTM) and User Adoption. You should be able to demonstrate how you've used telemetry and user feedback to pivot or accelerate a product.
- Squad Leadership: Experience leading a diverse team of Data Scientists, Full-stack/Front-end Developers, and Designers. You must be able to speak all their 'languages'.