ai engineer

Dealstitch AI builds AI agent workflows for private market investors, delivering production-grade systems that handle complex tasks.

• 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.

• 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;
• Nice to have: prior exposure to private markets, financial services, or enterprise data.

• Work with a senior team with 40+ years of combined private-market technology experience;
• Get direct access to decision-makers and see the impact of your work in weeks, not quarters.