01Role Overview
We are looking for a Full-Stack Engineer who can ship product features quick while using AI responsibly to increase velocity, quality, and consistency. This is not a role for someone who blindly accepts generated code. We need engineers who can use AI as leverage while still owning architecture, security, performance, testing, and maintainability.
You will build product features, internal tools, automation layers, code intelligence workflows, and developer experience improvements. You will also help shape how OneOrigin engineers use AI-assisted coding with discipline.
What you'll own:
- Build and ship full-stack features across React/Next.js, Node.js/Python, APIs, Postgres, and cloud services.
- Improve internal developer workflows using AI-assisted coding, repo indexing, code intelligence, scaffolding, and PR quality gates.
- Create internal coding copilots and repo-aware prompts aligned to OneOrigin conventions.
- Build automation around testing, linting, CI checks, documentation, and release confidence.
- Review AI-generated code for security, performance, edge cases, maintainability, and hidden assumptions.
- Partner with product, design, and AI teams to turn ambiguous requirements into clean product experiences.
- Document patterns, reusable components, and engineering playbooks.
What Success looks like:
- Features ship faster without reducing quality.
- AI-assisted development becomes structured, measurable, and repeatable.
- Engineering output improves because the system helps the team work better, not because people cut corners.
You should have:
- Strong full-stack fundamentals and production shipping experience.
- React/Next.js, TypeScript, Node.js or Python, APIs, Postgres, and Git.
- Solid testing discipline across unit, integration, and end-to-end scenarios where needed.
- Ability to debug deeply and explain tradeoffs clearly.
- Practical understanding of AI coding tools and their limitations.
Nice to Have:
MCP, internal developer platforms, monorepos, feature flags, code search, CI/CD automation, or AI code review workflows.
AI-Led Interview Focus:
You may be asked to review AI-generated code, identify risks, improve a feature design, or build a small workflow with AI assistance. We will look for engineering judgment, not just speed.
