What are the responsibilities and job description for the AI Infrastructure Engineer position at Hashlist?
We are hiring a Senior AI Engineer to work with a leading global automotive OEM, focused on building AI-powered tooling and infrastructure across the software development lifecycle. The role sits at the intersection of generative AI, developer tooling, SDLC automation, and scalable AI infrastructure, with automotive experience considered a strong advantage. The main focus is designing and deploying AI systems that automate the end-to-end engineering pipeline — from design through to validation — including the development of MCP (Model Context Protocol) servers and AI infrastructure that scales in production environments.
Engagement detail
- Location: San Francisco California
- Contract type: Permanent/Contract
- Start date: ASAP
- Work model: Hybrid
- Benefits: Competitive package; high-impact, high-visibility role within a major software-defined vehicle programme
Role focus
- Design and build AI-powered tooling integrated across the full SDLC ecosystem
- Architect end-to-end automation of the engineering pipeline, from design and development through to testing and validation, using generative AI
- Build, deploy, and maintain MCP (Model Context Protocol) servers as part of a scalable AI infrastructure strategy
- Develop AI systems that perform reliably and scale in production environments
- Collaborate with engineering, product, and infrastructure teams to embed AI capabilities into existing workflows and tooling
- Define and document AI system architectures, data flows, and integration patterns
- Evaluate emerging AI tooling and frameworks and provide recommendations to technical leadership
- Support the rollout and adoption of AI tooling across engineering teams
Requirements
- 5–6 years of hands-on experience building production-grade Generative AI systems
- Strong experience designing and building AI tooling and infrastructure — not just model usage, but the systems, pipelines, and infrastructure around them
- Proven experience with MCP servers and agentic AI architectures
- Track record of delivering scalable AI systems in complex, real-world engineering environments
- Deep understanding of SDLC processes and practical experience automating them with AI
- Proficiency in one or more programming languages commonly used in AI/ML engineering contexts
- Experience integrating AI tooling into CI/CD pipelines and developer workflows
Nice to have
- Experience in the automotive industry or adjacent regulated or complex engineering domains
- Familiarity with E2E automated testing pipelines and AI-assisted validation frameworks
- Experience with embedded software environments or vehicle software platforms
- Background working with multi-domain or cross-functional engineering teams
Next Steps
- Press "Apply"We will review your application
- If qualified, you will be accepted into the network and can be considered for this and similar positions