Technical Anchor

Ford Motor • Dearborn, MI

1d • Hybrid

About The Position

Ford Motor Company’s Global Data Insights & Analytics (GDIA) organization supports evidence-based decision making through data, analytics, and AI. Within the Strategy & Enterprise Analytics (SEA) team, the Technical Anchor owns the technical direction of data, analytics, and AI products, from foundational data capabilities through production generative AI applications. This role sets architecture and engineering standards across product teams, makes key technical trade-offs, and mentors engineers in delivering secure, reliable, and scalable solutions.

The Technical Anchor works with product managers, designers, data scientists, engineers, and business partners to clarify needs, explain technical trade-offs, and deliver measurable value. The position is hybrid, with a requirement to work onsite four or more days per week. The listed salary range is $68,300–$192,900; final grade and salary depend on candidate skills, experience, role scope, responsibility, and market value. Visa sponsorship is not available, and candidates must be legally authorized to work in the United States.

Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent practical experience.
• At least 5 years of experience in software or data engineering, including at least 2 years as a tech lead or architect on production systems.
• Strong skills in Python or Java and SQL, with experience building production services and REST APIs.
• Experience designing and running data pipelines or analytics products on a relational database or cloud data platform.
• At least 2 years of experience building, integrating, or putting generative AI or large language model applications into production.
• Experience deploying services to the cloud and establishing CI/CD, automated testing, and security scanning for a team.
• A track record of mentoring engineers and explaining technical decisions to technical and non-technical partners.
• Must be legally authorized to work in the United States; visa sponsorship is unavailable.

Nice To Haves

• Experience running ML models in production, including deployment, monitoring, and retraining.
• Experience developing RAG systems, agentic workflows, or multi-service AI applications using frameworks such as LangGraph, LlamaIndex, CrewAI, or equivalent.
• Experience building LLM evaluation, tracing, and observability to assess quality, safety, latency, and cost.
• Experience with data modeling, semantic layers, and BI tools.
• Experience with data governance, privacy compliance, and least-privilege access for data and AI systems.
• Experience leading a team’s adoption of AI coding assistants.
• Experience with Google Cloud Platform (GCP), including BigQuery, Cloud Run, GKE, Vertex AI, Pub/Sub, Cloud Logging, or Cloud IAM.
• Experience with Docker, Kubernetes, Terraform, and CI/CD tools such as Jenkins, Tekton, GitHub Actions, or Cloud Build.
• Experience with monitoring tools such as Dynatrace, Splunk, or Grafana.
• Experience with front-end frameworks such as React, Angular, or Vue.
• Experience in automotive, connected vehicle, regulatory compliance, or enterprise analytics environments.

Responsibilities

• Own the reference architecture, technical roadmap, and engineering standards for SEA data, analytics, and AI products.
• Review and approve architecture for new products and major changes, including data pipelines, analytics services, ML integrations, APIs, and user-facing applications.
• Lead the design of data models, semantic and reporting layers, and data pipelines to ensure analytics products are accurate, consistent, and maintainable.
• Lead delivery of production generative AI solutions, including retrieval-augmented generation (RAG), agentic workflows, and applications connected to approved enterprise data and tools.
• Own model selection and cost and latency budgets for AI services, and evaluate whether to build or buy AI tools and vendors.
• Set responsible AI standards, including evaluation, output validation, human review where appropriate, prompt-injection defenses, and safe handling of AI-generated code or SQL.
• Ensure sensitive and customer data is handled correctly, including access control, lineage, and privacy compliance.
• Set engineering practices across teams, including architecture and code reviews, automated testing, CI/CD, infrastructure as code, observability, ML model monitoring and retraining, and operational readiness.
• Lead productive use of AI coding assistants across teams, including practices, guardrails, and review standards.
• Mentor engineers, lead technical discussions, and develop technical depth across teams.
• Work with product managers, designers, data scientists, engineers, and business partners to clarify needs, explain trade-offs, and deliver measurable value.

Benefits

• Immediate medical, dental, vision, and prescription drug coverage.
• Paid parental leave, new parent ramp-up programs, and subsidized back-up child care.
• Family-building benefits, including adoption and surrogacy expense reimbursement and fertility treatments.
• 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.
• Generous vacation time, sick/personal time, and paid holidays, including between Christmas Eve and New Year’s Day.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior