Job Description
A venture-backed software company is building tools that help mission-driven organizations discover, track, and manage complex funding streams over long grant cycles. The product centralizes research, tracking, and collaboration so small teams can stay on top of dozens of live opportunities without drowning in spreadsheets or browser tabs. This role sits on a small AI-focused group that owns core systems for search, insights, and automation used by thousands of end users.
What Youll Do
Design, build, and ship production AI features that help users research opportunities, track requirements, and surface the next best actions, owning projects from prototype to production.
Own end-to-end pipelines that ingest unstructured external data, transform it into structured internal representations, and power semantic search and recommendations.
Manage embeddings and vector-backed services at scale, keeping indices healthy, fast, and cost-efficient as usage grows.
Develop evaluation and observability for AI features so they stay grounded, safe, and high-signal in real-world use.
Partner with product and other engineers to turn ambiguous user problems into clear technical projects, then ship iterative improvements quickly.
Qualifications
What were looking for
58 years of professional software engineering experience, including owning production services end to end in a fast-moving environment.?
Deep proficiency with Python in a modern backend stack, plus experience building scalable, reliable applications.?
Hands-on experience with modern LLMs and applied ML (RAG-style systems, embeddings, vector stores, and/or agentic workflows) in production, not just prototypes.?
Background at a product company where ML/AI is central to the user experience, ideally in a startup setting.?
Strong fundamentals, clear communication, and comfort collaborating closely with non-engineering stakeholders.?
Role details
Location: San Francisco Bay Area; expectation of regular in-person collaboration on a weekly basis.?
Work model: Hybrid, with a small, senior team that values experimentation, direct customer feedback, and rapid iteration.?
Impact: Your work will be used by organizations focused on education, conservation, and other long-term social and environmental initiati
Why Is This a Great Opportunity
Hypergrowth YC-backed startup
A venture-backed software company is building tools that help mission-driven organizations discover, track, and manage complex funding streams over long grant cycles. The product centralizes research, tracking, and collaboration so small teams can stay on top of dozens of live opportunities without drowning in spreadsheets or browser tabs. This role sits on a small AI-focused group that owns core systems for search, insights, and automation used by thousands of end users.
What Youll Do
Design, build, and ship production AI features that help users research opportunities, track requirements, and surface the next best actions, owning projects from prototype to production.
Own end-to-end pipelines that ingest unstructured external data, transform it into structured internal representations, and power semantic search and recommendations.
Manage embeddings and vector-backed services at scale, keeping indices healthy, fast, and cost-efficient as usage grows.
Develop evaluation and observability for AI features so they stay grounded, safe, and high-signal in real-world use.
Partner with product and other engineers to turn ambiguous user problems into clear technical projects, then ship iterative improvements quickly.
Qualifications
What were looking for
58 years of professional software engineering experience, including owning production services end to end in a fast-moving environment.?
Deep proficiency with Python in a modern backend stack, plus experience building scalable, reliable applications.?
Hands-on experience with modern LLMs and applied ML (RAG-style systems, embeddings, vector stores, and/or agentic workflows) in production, not just prototypes.?
Background at a product company where ML/AI is central to the user experience, ideally in a startup setting.?
Strong fundamentals, clear communication, and comfort collaborating closely with non-engineering stakeholders.?
Role details
Location: San Francisco Bay Area; expectation of regular in-person collaboration on a weekly basis.?
Work model: Hybrid, with a small, senior team that values experimentation, direct customer feedback, and rapid iteration.?
Impact: Your work will be used by organizations focused on education, conservation, and other long-term social and environmental initiati
Why Is This a Great Opportunity
Hypergrowth YC-backed startup