Applied AI Engineer

About the Role 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. What You'll Do 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 customer's 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. What We're Looking For 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. Compensation & Benefits Salary range: $175,000 to $300,000 USD annually. Equity included. Visa sponsorship is not available for this role. Location Hybrid, based in New York, NY . #J-18808-Ljbffr Wintermeyer Ventures