Job Title: Artificial Intelligence Senior Associate
Location: Dearborn, MI (Must be local)
Job Type: W2 Contract | NO C2C | NO CORP-TO-CORP
Expected hours per week: 40 hours per week
Schedule: Hybrid, 4 days onsite per week in Dearborn, MI
Pay Range: $65-68 an hour
Job Description:
Seeking an experienced Full Stack Software Engineer to join the Design, Cost & Complexity (DCC) team supporting data and AI products used across vehicle product development. This is a hands-on development role focused on building and delivering production-ready applications from front end through back end and data layers.
Key responsibilities include:
- Build and ship full-stack features using React, Python, APIs, relational databases, and Google Cloud Platform (GCP).
- Own features end to end, including design, development, testing, deployment, and production support.
- Develop and integrate AI/LLM-based features using AI coding tools, guardrails, evaluation, and human oversight.
- Design data models, APIs, integrations, and connections to existing engineering and legacy systems.
- Turn prototypes into secure, reliable, and maintainable production applications.
- Write automated tests and participate in code reviews, CI/CD, security, and observability practices.
- Work directly with engineers, product managers, technical program managers, and business users.
- Identify technical debt, risks, and quality concerns and recommend solutions.
- Support and mentor teammates and vendor engineers.
Required Qualifications:
- 5+ years of professional software engineering experience.
- Strong full-stack development experience.
- React.
- Python and/or Node.js.
- Relational databases such as PostgreSQL.
- Google Cloud Platform (GCP).
- AI/LLM development or hands-on use of AI coding tools.
- API design and data modeling.
- Automated testing, CI/CD, code review, and security best practices.
- Agile software development.
- Bachelor’s degree in Computer Science, Engineering, or a related field.
Preferred Experience:
- Agent frameworks, MCP, retrieval-augmented generation (RAG), or LLM evaluation.
- Automotive or manufacturing experience.
- Engineering tools involving design, simulation, testing, calibration, PLM, or manufacturing.
- Experience working with distributed or vendor teams.
- Master’s degree.
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