Rapidly prototype AI-powered products and features: take a concept from your Ventures Lead and deliver a working, demoable solution in 2–3 days.
Build end-to-end: frontend, backend, API integrations, and database—whatever it takes to get a prototype in front of a customer.
Integrate AI model APIs (OpenAI, Anthropic, Gemini, Azure) and build agentic workflows using function calling, tool use, and orchestration frameworks.
Build RAG pipelines that ground AI in domain-specific customer data using vector databases and embedding models.
Partner with portfolio company R&D teams to take validated prototypes into production—translating your fast-build into their architecture, standards, and infrastructure.
Participate in customer demos and POCs alongside your Ventures Lead, providing technical depth and fielding implementation questions.

1–4 years of professional experience in software engineering, applied AI, or product development—but what you’ve built matters more than tenure.
Demonstrated ability to take an idea from concept to working prototype independently.
Deep fluency in the AI tooling ecosystem—and the habit of staying current. You know about new releases before anyone asks you to look.
Clear communicator who can explain technical decisions to non-technical stakeholders and collaborate effectively with engineers across teams.
A track record of self-directed work: side projects, open-source contributions, hackathon wins, or entrepreneurial ventures carry significant weight.
Bonus: experience in SaaS, vertical market software, or early-stage startup environments.

AI Product Engineer

Key skills