AI Engineer

The role

This company builds and licenses AI agents that automate critical customer lifecycle workflows for major financial institutions. They run real agentic systems in production, tackling long, high-stakes banking processes. Backed by leading VCs, they're scaling rapidly with significant traction.

This is not a siloed research role. You will own the infrastructure that keeps these production agents reliable: the evals, feedback loops, prompt engineering, and fallbacks. You'll also design the human-in-the-loop logic, deciding when an agent acts and when a person steps in. It's a product-leaning seat, blending AI engineering with pragmatic ML, building across the full agentic and software stack.

• Design and implement agent reliability infrastructure, including evals, feedback loops, prompt engineering, and fallbacks.
• Build and maintain human-in-the-loop decision logic for high-stakes agent actions.
• Take ownership of proprietary supervised and self-supervised ML models, applying recent academic work pragmatically.
• Contribute across the full agentic and software stack, including Node and Type Script.
• Shape the evolving data strategy for production AI agents in a rapidly growing environment.

• Production experience building and maintaining agentic or LLM infrastructure: evals, feedback loops, prompt engineering, fallbacks, and human-in-the-loop decision logic.
• A pragmatic ML foundation across supervised and self-supervised methods.
• Product-leaning and full-stack in mindset; comfortable contributing to a Node and Type Script software stack.
• Strong system design capabilities, with proven adaptability in a technical assessment (e.g., Type Script).
• Thrives in a fast-paced startup environment, executing at pace and owning your lane while data strategy evolves.