AI Engineer (Agent Systems)
San Francisco (hybrid / in-office preferred)
Early-stage, post-PMF (~20 people)
B2B SaaS / AI / Enterprise workflows
$200-$300k base salary
About the Company
We’re building domain-specific AI agents that automate complex, high-stakes enterprise workflows in a regulated, trillion-dollar industry. Our systems are used in real production environments by large enterprise customers and are already driving meaningful revenue growth.
The company is well-funded, growing quickly, and led by a highly technical founding team with prior startup and big-tech experience. This is a hands-on role with real ownership and direct product impact.
The Role
We’re looking for an AI Engineer to help design, evaluate, and productionize AI agent systems. This is not a model training or research role. You’ll focus on making agents reliable, measurable, and useful in real-world workflows.
You’ll work across experimentation, tooling, and infrastructure to help agents reason, act, and improve over time in production.
What You’ll Do
- Build end-to-end evaluation frameworks to measure and improve agent performance
- Experiment with modern agentic techniques (e.g. multi-agent systems, feedback loops, reasoning-from-feedback)
- Design and implement lightweight orchestration layers, services, and internal tools that enable agents to operate reliably
- Translate emerging research and ideas into practical production experiments
- Work closely with product and leadership to ship quickly and iterate based on real customer usage
What We’re Looking For
- Strong Python experience and comfort building production systems
- 2–4+ years of hands-on ML / AI experience, ideally in applied or product-focused roles
- Experience owning systems end-to-end, from early prototypes to production
- Clear communicator who can reason through tradeoffs and explain decisions
- High ownership mindset — comfortable operating with ambiguity and moving fast
Nice to Have
- Experience at an early-stage startup (0→1 or first ~30 engineers)
- Background in B2B SaaS or enterprise software
- Prior founder or early engineer experience
- Advanced degree in AI/ML (can offset years of experience)
What This Is Not
- Not a research scientist or paper-focused role
- Not primarily model training or fine-tuning
- Not a slow-paced or low-ownership environment
Why This Role
- Real production impact with enterprise customers
- Significant ownership over core AI systems
- Opportunity to help define how AI agents work in high-stakes workflows
- Strong growth trajectory and meaningful career upside
