Applied AI Engineer

This is a foundational engineering role on the agentic platform that every product team builds on. You will own the infrastructure evals and context engineering that make AI agents reliable enough for healthcare finance where accuracy is non-negotiable. Your work will ship directly into customers hands and set the standard for how new capabilities are added across the platform.

• Define and standardize tool connector and skill contracts (MCP-style) so new capabilities can be added continuously without destabilizing the platform.
• Build the connective tissue so agents tools context and data compose cleanly across products matching the right architecture to each use case.
• Build production-grade eval harnesses replay pipelines and benchmarks and gate every release on them.
• Ground agents in each customers business rules and data and build the control loops that keep outputs reliable.
• Fine-tune in-house and open-source models benchmark against frontier baselines and make informed build-vs-buy decisions.

• 5 to 10 years of experience in applied AI or ML engineering roles.
• Proven track record building and deploying agentic AI systems in production including evals harnesses context engineering and tool surfaces.
• End-to-end experience at high-growth AI or technology companies with demanding engineering standards.
• Rigorous ML foundations with a deep understanding of LLM model architecture and training beyond framework-level knowledge.
• Strong CS fundamentals; a degree in Computer Science Mathematics ML or Statistics from a well-regarded program.
• Hands-on experience with relational data modeling.
• Proficiency in Python and familiarity with GCP and Vertex AI.
• Experience with RAG embeddings and LLM fine-tuning workflows.

Salary range: $175000 to $300000 USD annually. Equity included. Visa sponsorship is not available for this role.

Hybrid based in New York NY.