Applied AI Engineer

Wintermeyer Ventures; New York (NY); Hybrid; USD 175,000 - 300,000; Full time

Benefits offered by this job

Equity included

Job summary

Wintermeyer Ventures in New York, NY is seeking a foundational engineering role focused on the agentic platform. You will own the infrastructure, evals, and context engineering that make AI agents reliable for healthcare finance, with outputs shipping directly to customers and setting platform-wide standards.

You will define contracts, build connective tissue across tools and data, and gate releases with production-grade evals.

Qualifications

• 5 to 10+ years in applied AI/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.
• 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.

Responsibilities

• 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.

Skills

Applied AI/ML engineering

Agentic AI systems

Python programming

Relational data modeling

LLM architecture & training

High-growth tech environment

Education

B.S./M.S. in Computer Science, Mathematics, ML, or Statistics

Tools

GCP

Vertex AI

LLM fine-tuning workflows

Embedding techniques

Job description

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.