AI Engineer Lead

About The Role

You'll own the engineering behind our AI agent work end to end, taking AI from discovery to into production systems that move the needle on real work for private market investors. You'll set the technical direction, ship the hard parts yourself, and raise the bar for how we build.

What you'll do

• Lead the build end to end, from scoping the highest-leverage agent use cases to shipping and hardening them in production.
• Design and build production-grade AI agents that use tools and run multi-step agentic workflows on LLM APIs from Anthropic and OpenAI, grounded in retrieval over a client's own documents and data.
• Stand up the supporting infrastructure, including vector search, data pipelines, evaluation harnesses that measure agent quality, and observability for agents running in production.
• Integrate agents with the systems a firm already runs by wiring up APIs and enterprise authentication such as SSO, SAML, and OAuth, while meeting their security and compliance bar.
• Evaluate AI-native tools and traditional systems with deep technical rigor, and make the call on what to use.
• Set engineering standards and mentor other engineers.

What we're looking for

• 5+ years of software engineering experience shipping production systems, with strong Python and TypeScript.
• Hands-on experience building LLM applications, including agent orchestration and tool use, retrieval-augmented generation, vector databases such as Pinecone, Weaviate, or pgvector, prompt engineering, and evals.
• A track record of taking AI systems into messy, real-world environments and making them work, including the integration and security work that enterprise deployments demand, from REST and GraphQL APIs to SSO, SAML, and IAM.
• Comfort leading in ambiguous, fast-moving environments and owning outcomes end to end.
• Bonus: prior exposure to private markets, financial services, or enterprise data.

Why Dealstitch

We're a senior team with 40+ years of combined private-market technology experience. You'll work on problems that matter, with direct access to decision-makers, and see the impact of your work in weeks, not quarters.