Senior Product Engineer (AI)

About the role

We build AI-native workflows that help nonprofits move faster, make better decisions, and raise more for the causes they serve. This role turns product ideas into working prototypes quickly. When an idea proves valuable, you make it secure, reliable, and ready to scale. You’ll join a small team where everyone builds. You work with product, engineering, data, and customer-facing teams to explore new AI workflows, test what works, and ship the best ideas into our products and internal systems.

It suits someone who likes autonomy, builds fast, thinks about users, and knows when a prototype needs to become production software.

Responsibilities

• AI-powered product features. Design and build new AI experiences across our products: agentic workflows, research assistants, natural-language interfaces, human-in-the-loop review, recommendation flows, and workflow automation for nonprofit teams. One example is ProspectAI, our deep-research agent, used by hundreds of nonprofits today. You will help drive its speed, cost, quality, and reliability at scale.
• Rapid experimentation. Take a loosely defined opportunity, find the smallest useful experiment, and build it fast. You will prototype with LLMs, internal data, third-party APIs, and product interfaces. You will test with real users, and help decide what to kill, iterate, or scale.
• Prototype to production. When an experiment works, make it real. This means secure architecture, reliable data flows and pipelines, observability, permissions, cost and latency controls, and code that others can maintain.
• Evals and measurement. We measure what we ship. You will build the eval harnesses, instrumentation, and experiment scaffolding that tell us whether a feature works. This applies before launch, after launch, and every time a prompt, model, or pipeline changes. You will work with a PM who sets the measurement direction and expects evidence over opinion.
• Hard data problems. Our most valuable problems are messy-data problems: churn prevention, entity matching, data quality, and donation propensity across large, noisy datasets. You will also build AI-powered internal tools that create leverage across engineering, product, and customer-facing teams.

Requirements

• Strong product engineering experience across full-stack web applications: frontend, backend, APIs, data flows, and third-party integrations
• AI or LLM features you have shipped to real users, with a practical grasp of evaluation, prompt and workflow iteration, failure modes, and cost and performance tradeoffs
• Strong Python or TypeScript, or both
• AI-native ways of working. You use AI agents and tools as a core part of how you build, and it makes you fast
• Product judgment. You care about user value more than technical novelty, and you ship, learn, and improve
• Comfort with messy data. You do not need a data science title, but these problems should interest you rather than put you off

Nice to have

• Agentic workflows, RAG, eval harnesses, AI observability, or human-in-the-loop systems
• Applied ML or a data science background, or work on data-heavy products, CRM data, or prospect research
• Startup or founding-engineer experience in high-ambiguity product work

Why this role matters

You will shape how Dataro uses AI across our products and how we work. You get room to experiment, and the responsibility to make the good ideas real. The best work here is not AI for its own sake. It is thoughtful product engineering, at real scale, for nonprofits.