Full Stack Engineer
150k – 250kSan Francisco, CAFullstack EngineeringOnsite2+ YOE
Summary
Build and own full-stack features end-to-end on Next.js and Python for an AI memory platform. Requires 2+ years shipping production web apps, strong Python and modern frontend skills, and comfort operating production systems.
About the role
What You'll Do
- Ship end-to-end features: Design APIs, build UIs, write backend logic, own data models, and deploy to production.
- Build for scale & speed: Optimize latency, caching, and query patterns; keep pages snappy and backends reliable.
- Own quality: Write tests, enforce typing/linting, review PRs, and maintain clean, well-documented code.
- Collaborate deeply: Work with Design for great UX, with Research to integrate new memory capabilities, and with customers to refine requirements.
- Operate what you build: Add observability, set alerts, debug prod issues, and drive continuous improvements.
- Lead with product sense: Prioritize ruthlessly, make tradeoffs explicit, and iterate based on data and feedback.
- Go beyond your lane: Unblock teams, learn new tools on the fly, and do what it takes to deliver.
Minimum Qualifications
- 2+ years proven experience shipping full-stack web applications at scale. Our stack is Next.js/React and Python.
- Strong Python skills and familiarity with modern web stacks (REST/GraphQL, Postgres, Redis, Celery/queues).
- Solid front-end chops: component architecture, state management, forms, accessibility, SSR/ISR.
- Track record of owning features E2E: from design docs to rollout and post-launch iteration.
- Code quality mindset: testing (unit/integration), type safety (TS/pyright/mypy), CI/CD, and thoughtful review culture.
- Excellent communication and teamwork; comfortable working cross-functionally with design, research, and GTM.
- Comfortable operating production systems (logs, metrics, tracing) and meeting low-latency requirements.
- No CS Degree required—we care about impact and craftsmanship.
Nice to Have
- Experience integrating LLM/memory features (RAG, embeddings, vector DBs) into products.
- Familiarity with vLLM, model serving, or lightweight ML infra integrations.
- Real-time features (WebSockets/Server Actions/streaming), file uploads, and background jobs at scale.
- Infra awareness: Docker, IaC, basic K8s/Vercel/AWS/GCP deployment patterns and cost thinking.
- Product/UI polish: Tailwind/Design Systems, charts, empty states, error UX, and performance budgets.
- Security & privacy basics (PII handling, audit/logging).
Skills
Next.jsReactPythonRESTGraphQLPostgreSQLRedisCeleryTypeScriptCI/CDDockerKubernetesTailwind CSSWebSocketsRAG
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