Backend Engineer

Mem0 • San Francisco Bay Area, CA

1d • Onsite

About The Position

Role Summary: Own the backend that powers Mem0’s memory platform. You’ll design clean REST APIs, model data across relational and graph stores, and operate services in production. When customers hit issues, you’ll chase them down to root cause, ship fixes, and harden the system—while collaborating tightly with frontend and research to deliver fast, reliable features. About Mem0 We're building the memory layer for AI agents. Think long-term memory that enables AI to remember conversations, learn from interactions, and build context over time. We're already powering millions of AI interactions. We are backed by top-tier investors and are well capitalized. Our Culture Office-first collaboration - We're an in-person team in San Francisco. Hallway chats, impromptu whiteboard sessions, and shared meals spark ideas that remote calls can't. Velocity with craftsmanship - We build for the long term, not just shipping features. We move fast but never sacrifice reliability or thoughtful design - every system needs to be fast, reliable, and elegant. Extreme ownership - Everyone at Mem0 is a builder-owner. If you spot a problem or opportunity, you have the agency to fix it. Titles are light; impact is heavy. High bar, high trust - We hire for talent and potential, then give people room to run. Code is reviewed, ideas are challenged, and wins are celebrated—always with respect and curiosity. Data-driven, not ego-driven – The best solution wins, whether it comes from a founder or an engineer who joined yesterday. We let results and metrics guide our decisions.

Requirements

• 3+ years building backend systems and shipping REST APIs to production.
• Strong Python fundamentals; experience with async programming and a major web framework (FastAPI/Django/Flask).
• Solid data modeling and SQL skills; hands-on with query tuning and performance debugging in Postgres/MySQL.
• Experience with graph databases (e.g., Neo4j or Amazon Neptune) and appropriate data modeling trade-offs.
• Comfortable running services on AWS with Docker and Kubernetes.
• Demonstrated root-cause analysis and ownership from incident to prevention.
• Clear communicator and effective collaborator with frontend, research, and customers.

Nice To Haves

• GraphQL/gRPC; event-driven systems (SNS/SQS/Kafka) and background workers (Celery/RQ).
• Caching, rate limiting, multi-tenancy, and feature-flag strategies.
• Security & privacy best practices (PII handling, secrets management).
• Deep observability experience (OpenTelemetry, SLO-based alerting).
• Prior work with search/retrieval or memory systems.
• On-call experience and running blameless postmortems.

Responsibilities

• Design & ship REST APIs: Define contracts, versioning, auth, rate limits; write migrations and docs.
• Model data & schemas: Relational (Postgres) and graph (e.g., Neo4j); enforce integrity and performance.
• Debug customer issues end-to-end: Trace with logs/metrics/traces, reproduce, fix, and write preventative guardrails.
• Optimize performance: Tune slow SQL with EXPLAIN/ANALYZE , indexes, partitioning, pagination, and caching (e.g., Redis).
• Build services in Python: Async where it helps (FastAPI/Starlette, Django/DRF, Flask), background jobs, queues, schedulers.
• Operate in the cloud: Containerize with Docker , deploy on Kubernetes (EKS), and use AWS primitives (EC2, RDS/Aurora, S3, IAM).
• Instrument everything: Custom metrics, structured logging, tracing; set SLOs and alerts (CloudWatch/Prometheus/OpenTelemetry).
• Collaborate & ship: Work with frontend and research to scope APIs and deliver features to production.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed