Technical Anchor

Ford Motor Company • Dearborn, MI

1d • $68,300 - $192,900 • Hybrid

About The Position

As part of Ford’s Global Data Insights & Analytics (GDIA) organization, the Strategy & Enterprise Analytics (SEA) team develops data, analytics, and AI products that help teams make informed decisions and deliver meaningful outcomes. The Technical Anchor owns the technical direction of these products, from data and analytics foundations to production generative AI applications. This role sets architecture and engineering standards across SEA product teams, makes key technical trade-offs, and mentors engineers to deliver secure, reliable, and scalable solutions.

The position works with product managers, designers, data scientists, engineers, and business partners to clarify needs, explain trade-offs, and deliver measurable value. It is hybrid, with a requirement to be onsite four or more days per week.

Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent practical experience.
• 5+ years of experience in software or data engineering, including 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.
• 2+ years of experience building, integrating, or putting generative AI or large language model applications into production.
• Experience deploying services to the cloud and setting up 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; employment eligibility will be verified at hire.
• Visa sponsorship is not available.

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 with 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 the architecture of 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.
• Lead delivery of production generative AI solutions, including RAG, agentic workflows, and applications connected to approved enterprise data and tools.
• Own model selection, AI-service cost and latency budgets, and build-versus-buy evaluations of AI tools and vendors.
• Set responsible AI standards for evaluation, output validation, human review where appropriate, prompt-injection defenses, and safe handling of AI-generated code or SQL.
• Ensure products handle sensitive and customer data appropriately through 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 teams’ productive use of AI coding assistants, including practices, guardrails, and review standards.
• Mentor engineers, lead technical discussions, and grow 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 and new parent ramp-up programs
• 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
• Employee resource groups
• Paid time off for individual and team community service
• 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