AI Engineering Tech Lead

About

My client is a growth-stage enterprise software company with AI at the core of their product. They have raised significant venture funding, with a new round on the horizon, and are actively hiring while much of the market is cutting. Their customers include major enterprises, and the product sits at the intersection of developer tooling and applied AI.

They are hiring an AI Engineering Tech Lead to own and advance the AI capabilities that power their platform. This is a hands-on individual contributor role. You will write code, build models, and deploy your own work to production. This is not a management, architect, or strategy-only position.

What You Will Do

• Designing and building AI/ML features end-to-end, from experimentation through production deployment
• Bridging classical machine learning techniques with modern LLM-powered approaches, bringing scientific rigor to evaluation, testing, and iteration
• Building and optimizing LLM-powered features including natural language interfaces, data summarization, and intelligent exploration tools
• Designing evaluation frameworks, prompt engineering strategies, and experiment tracking systems to ensure measurable model improvement
• Owning the full deployment lifecycle for AI features, including containerization, Helm charts, and production infrastructure
• Collaborating with product, engineering, and data teams to integrate AI seamlessly into an enterprise SaaS platform
• Staying current with the latest AI research and tools, identifying opportunities to apply new techniques to real product problems

What You Bring

• Staff, Principal, or Tech Lead level individual contributor who still writes code daily and thrives with high autonomy
• 5+ years of experience in AI and ML engineering, with hands-on work shipping features to production
• A classical machine learning foundation combined with strong LLM or agent engineering skills (evaluation frameworks, fine-tuning, or custom architectures optimized for latency, cost, and performance)
• A track record of building and deploying AI/ML features end-to-end in a production environment, not handing off to another team
• Comfort with Docker, Kubernetes, and Helm charts, with the ability to take ML/AI work into production yourself
• Experience working on enterprise SaaS products with attention to performance, security, and multi-tenancy
• Authorization to work in the United States (this role does not offer near-term visa sponsorship)

This Role Is Not

• A management position. You will not be leading or scaling an engineering team.
• A pure research role. You ship production code, not papers.
• An MLOps or infrastructure-only role. You build the AI features, not just the pipelines that serve them.
• An architect role. You design systems and you build them yourself.

Bonus Points

• Experience at an early-stage startup or on a small, fast-moving team within a larger company
• Familiarity with developer tooling, agentic workflows, or AI-native product development
• Background with experiment tracking systems like MLflow or Weights & Biases
• Degree in Computer Science, Mathematics, Data Science, or a related field (practical experience valued equally)

Why Join

• Real influence over how the company approaches AI. This is not an execution-only role.
• Multiple active AI initiatives spanning both classical ML and cutting-edge agentic work. You will help shape the direction.
• A strong engineering team with deep experience building together. These are genuinely great people who respect each other's contributions.
• A rare balance of classical ML work, applied AI, and production software engineering in one role.
• The company is growing rapidly and actively hiring. New funding round approaching, with strong enterprise traction.

Logistics

• Location: Bay Area, CA (in-office)
• This is a full-time W-2 position. No C2C or contract engagements.

Equal Opportunity Employer

My client is an equal opportunity employer. They celebrate diversity and are committed to building an inclusive team. Candidates of all backgrounds are encouraged to apply, and they do not discriminate on the basis of race, color, religion, gender identity, sexual orientation, age, disability, national origin, or any other protected characteristic.