# AI Engineering Lead **Company**: Ford Motor Company **Location**: Dearborn, MI **Work arrangement**: hybrid **Experience**: senior **Job type**: full-time **Salary**: $85,400-$192,000 **Category**: IT **Industry**: Automotive **Wikidata**: https://www.wikidata.org/wiki/Q44294 **Apply**: https://efds.fa.em5.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/70285?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_b4b55016-78d ## Description As the AI Engineering Lead, you will architect, build, and scale AI-powered solutions that accelerate both the delivery of Integrated Services Data, AI & Analytics (ISDAIA) products and the adoption of AI capabilities across the Integrated Services business. You will lead the development of enterprise-grade AI applications, agentic systems, copilots, retrieval-augmented generation (RAG) solutions, and intelligent workflow automation that transform how teams discover insights, make decisions, and deliver value. This role combines hands-on technical leadership with product thinking and strategic execution. You will partner closely with Product Managers, Engineering Teams, Analytics Leaders, and Business Stakeholders to identify high-value use cases, develop reusable AI capabilities, and enable responsible AI adoption at scale. You will play a key role in shaping the future AI ecosystem for Integrated Services by building scalable frameworks, shared services, and AI-enabled experiences that improve business outcomes, operational efficiency, and speed to delivery. ## Responsibilities ### Strategic Thinking & Leadership - Partner with business leaders and product teams to identify high-value AI opportunities and translate them into scalable AI-powered solutions. - Define and communicate AI solution vision, roadmaps, and measurable success metrics. - Drive AI strategy across Generative AI, Agentic AI, conversational experiences, AI-enabled analytics, and intelligent automation initiatives. - Establish governance frameworks for Responsible AI, security, compliance, scalability, and enterprise adoption. - Lead cross-functional AI programs and influence executive stakeholders through compelling business cases, demonstrations, and measurable outcomes. ### Technical Leadership & Expertise - Architect and oversee end-to-end AI solutions, including: - Conversational AI and Copilot experiences - Retrieval-Augmented Generation (RAG) architectures - Agentic AI frameworks and multi-agent orchestration systems - AI-powered analytics and insight generation solutions - Natural language interfaces for analytics and business intelligence - Intelligent workflow automation and decision-support capabilities - Semantic search and enterprise knowledge management solutions - Strong proficiency in Google Cloud Platform (GCP) services for AI development (Vertex AI, BigQuery, Cloud Storage, Dataflow). - Experience designing and deploying enterprise AI solutions leveraging Large Language Models (LLMs), foundation models, prompt engineering, and model evaluation frameworks. - Experience building AI systems using Python-based ecosystems and modern AI frameworks. - Experience with vector databases, embeddings, semantic search, grounding techniques, and retrieval architectures. - Implement scalable AI Engineering, MLOps, and LLMOps practices including CI/CD, prompt versioning, testing, governance, monitoring, and lifecycle management. - Proficiency in Git, Docker, API-based deployments, cloud-native architectures, and scalable AI services. - Apply strong software engineering practices including modular design, testing, observability, security, and documentation. - Establish reusable AI frameworks, accelerators, and engineering patterns that improve speed, consistency, and quality of delivery. - Evaluate emerging AI technologies and identify opportunities to accelerate analytics delivery and business adoption. - Support architectural reviews and ensure best practices across AI systems, platforms, and products. - Implement Responsible AI principles including governance, explainability, privacy, security, and ethical AI compliance. ### Delivery Focus - Own end-to-end AI solution delivery in partnership with Product, Engineering, Data, and Business teams. - Ensure production-grade deployment of AI applications, copilots, and agent-based solutions using containerization, orchestration, and scalable cloud infrastructure. - Build reusable AI accelerators, frameworks, and services that improve speed-to-delivery across the ISDAIA portfolio. - Partner with product teams to embed AI capabilities directly into dashboards, self-service analytics platforms, applications, and business workflows. - Influence investment decisions using measurable business impact, adoption metrics, operational efficiencies, and ROI analysis. - Establish monitoring frameworks for AI performance, solution effectiveness, reliability, governance, and user adoption. ### Team Development & Community Leadership - Lead and mentor AI engineers while establishing best practices for enterprise AI development. - Build AI engineering standards, reusable frameworks, shared tooling, libraries, and delivery patterns across ISDAIA. - Promote knowledge sharing through Communities of Practice and AI Centers of Excellence. - Foster a culture of experimentation, continuous learning, innovation, and engineering excellence. - Support talent development in emerging AI disciplines including Generative AI, Agentic AI, conversational experiences, and intelligent automation. - Serve as a thought leader for enterprise AI adoption and AI-enabled transformation initiatives. ## Qualifications ### Minimum Requirements - Bachelor’s Degree in a related field (Computer Science, Artificial Intelligence, Data Science, Engineering, Information Technology, or equivalent). - 5 to 8 years of experience delivering enterprise software, analytics, data, or AI solutions. - 5+ years of experience using Python-based development technologies and modern software engineering practices. - 3+ years of experience designing, deploying, and supporting AI/ML or Generative AI solutions in production environments. - Experience building and deploying Generative AI, conversational AI, Copilot, or agent-based solutions. - Experience acting as a senior technical lead facilitating solution trade-offs and architectural decisions. - Experience using Cloud AI Platforms (GCP preferred). - Strong understanding of APIs, cloud-native architectures, CI/CD pipelines, and enterprise application development. - Hands-on experience with Generative AI technologies, Retrieval-Augmented Generation (RAG), and enterprise AI deployment. ### Preferred Requirements - Master’s Degree in Artificial Intelligence, Computer Science, Data Science, Engineering, or related field. - Experience managing and growing high-performing AI engineering teams. - Experience developing enterprise copilots, AI assistants, agent-based systems, and intelligent automation solutions. - Experience implementing Retrieval-Augmented Generation (RAG) architectures, vector databases, semantic search, and knowledge-grounding strategies. - Strong working knowledge of GCP and enterprise AI architecture patterns. - Expertise in open-source technologies such as Python, LangChain, LangGraph, Semantic Kernel, SQL, Spark, and modern AI development frameworks. - Experience working with Vertex AI, OpenAI, Anthropic, Gemini, or comparable enterprise AI ecosystems. - Experience building reusable AI platforms, accelerators, frameworks, and enablement capabilities. - Experience deploying AI solutions into business workflows, analytics products, self-service insights platforms, or decision-support solutions. - Experience implementing Responsible AI, AI governance, MLOps, and LLMOps practices at enterprise scale. ## Benefits - Immediate medical, dental, vision and prescription drug coverage - Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more - Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more - Vehicle discount program for employees and family members and management leases - Tuition assistance - Established and active employee resource groups - Paid time off for individual and team community service - A generous schedule of paid holidays, including the week between Christmas and New Year's Day - Paid time off and the option to purchase additional vacation time ## Skills ### Required - Python - Google Cloud Platform (GCP) - Vertex AI - BigQuery - Cloud Storage - Dataflow - Large Language Models (LLMs) - foundation models - prompt engineering - model evaluation frameworks - vector databases - embeddings - semantic search - grounding techniques - retrieval architectures - Git - Docker - API-based deployments - cloud-native architectures - scalable AI services ### Nice to have - Master’s Degree in Artificial Intelligence - Experience managing and growing high-performing AI engineering teams - Experience developing enterprise copilots - AI assistants - agent-based systems - intelligent automation solutions - Retrieval-Augmented Generation (RAG) architectures - knowledge-grounding strategies - GCP - enterprise AI architecture patterns - open-source technologies - LangChain - LangGraph - Semantic Kernel - SQL - Spark - modern AI development frameworks - OpenAI - Anthropic - Gemini - comparable enterprise AI ecosystems --- Source: [Apply at efds.fa.em5.oraclecloud.com](https://efds.fa.em5.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/70285?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)