Job Opportunities API

Who We Are Open Government Products (OGP) operates like a startup within the government; We are a fast-paced, dynamic team of engineers, designers, and product managers dedicated to public good. We autonomously identify opportunities to solve public problems using tech, rapidly prototype, and launch solutions — from citizen apps to automating public agency operations. Embracing an open-sourced and flat hierarchy, we cut through bureaucracy to focus on real-world, user-centric innovations that drive change. The Team We're hiring for the AI Native team. Our mandate: rethink how product development happens across OGP, with AI at the centre of how people work. We work with product teams and with OGP's central tooling team. We build shared AI tooling on top of existing infrastructure and help product teams adopt it across how they code, plan, and operate. Our success metric: teams across OGP move faster because of how they use AI in their workflow. About the Role Something is shifting in how software gets built. Stripe ships 1,300+ pull requests per week written by autonomous coding agents, built on infrastructure their engineers created years before LLMs existed. Anthropic reports 70-90% of their code is AI-written . Uber's engineers run multiple background agents in parallel and review the pull requests when they land. The companies seeing the largest gains aren't the ones with the best models. They're the ones that redesigned their workflows, restructured their teams, and rebuilt their culture around a new division of labour between humans and AI. The gap between "we should use AI" and "we shipped it" is where we operate. You'll work across product teams to figure out where AI fits their workflow, build the right tooling, and get it running. If your background is a better fit for another engineering team at OGP, we may reach out to discuss those opportunities as part of the hiring process. What you'll do Build shared AI tooling. Secure sandbox runtimes, evaluation harnesses, model gateways, prompt management, internal MCP servers. You'll work with OGP's engineering tooling team to extend the developer infrastructure that product teams already depend on, adding the AI layer on top. You'll treat these as internal products: talk to the engineers who use them, write clear docs, iterate on feedback. Work alongside product teams. You'll help teams adopt AI-native workflows into how they build and ship. That could mean setting up coding agents and AI-assisted review, or rethinking how a team plans and tracks work. The goal: the team ships their next feature faster because of how they now work. Stay ahead of the curve. Between engagements, you'll investigate new models, tools, and techniques. You'll pick what's worth adopting and sell it to the team. The AI tooling landscape moves fast; we need to be tracking it. What we're looking for You've shipped and maintained production software. You've built systems real users depend on, dealt with deployments and incidents, and carried the maintenance that follows a launch. You're fluent across the stack: cloud infrastructure, containers, databases, API design. Working inside other teams' live codebases should feel familiar. You've built developer-facing tooling. CI/CD pipelines, internal libraries, developer CLIs, APIs, platform services. You've shipped tools other engineers use, whether at work or on side projects. Ideally you've worked on things like model gateways, sandbox runtimes, eval harnesses, or MCP integrations. You build on top of LLMs. You already code with Claude Code, Cursor, Copilot, or similar. You've built with LLM APIs — and pushed further into agent architectures, prompt management, tool-use orchestration, or eval pipelines. You have opinions about where autonomous agents work and where they fall apart, formed through use and built-up conviction. You learn fast and don't need things spelled out. The AI tooling landscape shift