Builds end-to-end features for Mem0's memory platform using Next.js/React for UI and Python for backend, optimizing for scale, speed, and reliability. Collaborates with design, research, and customers while owning production operations and code quality.
150k – 180k/yr
On-siteFullstack Engineering
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
Proven experience shipping full-stack web applications at scale using 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.
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.
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