AI Platform Engineering Manager (Data & Insights)

At Ford, data and artificial intelligence are the engines powering the company's transformation. This role sits within the Data Platforms Engineering (DPE) organization and is distinct from traditional ML platform roles; rather than training models for the enterprise, this position focuses on operationalizing AI within the data platform itself. The goal is to make enterprise data understandable, discoverable, and usable for every team—from supply chain to marketing—by weaving AI into the fabric of how the workforce interacts with data.

• Reimagine Data Access: Lead the engineering of AI-powered features, such as intelligent agents and natural language interfaces, that allow users to 'talk to their data.'
• Empower Ford Teams: Build systems that transform structured and unstructured data into actionable insights for non-technical users.
• Technical Leadership: Guide and grow a high-performing engineering team to build scalable, secure, and intelligent platform capabilities.
• Operationalize Multi-Agent AI: Design collaborative agents that interpret user questions, identify relevant datasets, and generate analysis within a secure environment.
• Cross-Functional Collaboration: Partner with data governance, metadata, provisioning, and quality teams to deliver seamless AI-enabled experiences aligned with enterprise standards.
• Responsible Innovation: Ensure all AI solutions are ethical, explainable, and bias-aware while meeting regulatory and privacy requirements.

• Experience: 10+ years of engineering experience, including 5+ years building data or AI-centric platforms at scale.
• Technical Expertise: Deep knowledge of large-scale distributed systems, API-driven architectures, and cloud-native platforms (GCP preferred).
• AI Specialization: Hands-on experience with LLMs, vector databases, orchestration engines, and agent frameworks (e.g., LangChain, Haystack, Semantic Kernel).
• Leadership: Proven ability to lead engineering teams with a focus on impact, velocity, and quality.
• Product Mindset: Ability to collaborate with product managers and user researchers to create user-centric features.
• Enterprise Knowledge: Experience in regulated environments with a strong understanding of security, compliance, and governance.
• Core Values: A passion for data accessibility, digital equity, and user-centric design.