Artificial Intelligence Engineer

Early-stage, post-PMF (~20 people) B2B SaaS / AI / Enterprise workflows 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 #J-18808-Ljbffr