Role Summary
Own the backend that powers Mem0's memory platform. You'll design clean 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. You'll work closely with frontend and research to deliver fast, reliable features.
This isn't a typical SaaS backend role. You're building the infrastructure that stores and retrieves long-term memory for AI agents. Every API you design, every query you tune, and every schema decision you make directly affects how well AI can remember and reason.
What You'll Ship Early
First 30 days: Deeply understand the memory platform architecture. Ship your first meaningful backend change to production, whether that's a bug fix, performance improvement, or new API endpoint.
First 60 days: Own a backend workstream end-to-end. Have a clear picture of where the bottlenecks and reliability gaps are, and be actively fixing them.
First 90 days: Be a trusted owner of core backend systems. The team comes to you when something breaks, and you've already made it harder to break.
What You'll Do
Design and ship APIs. Define contracts, versioning, auth, rate limits. Write migrations and docs.
Model data and schemas. Relational (Postgres) and graph (e.g., Neo4j). Enforce integrity and performance as data grows.
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 (Redis). Care about p99 latency, not just averages.
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 and ship. Work with frontend and research to scope APIs and deliver features to production.
Minimum Qualifications
3+ years building backend systems and shipping 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 Have
GraphQL/gRPC. Event-driven systems (SNS/SQS/Kafka) and background workers (Celery/RQ).
Caching, rate limiting, multi-tenancy, and feature-flag strategies.
Security and 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.
Compensation
Salary: $150K to $250K base (depending on experience)
Equity: 0.10% to 0.50%
Location: San Francisco (in-person)
About Mem0
We're building the memory layer for AI agents. Long-term memory that lets AI remember conversations, learn from interactions, and build context over time. We already power millions of memory operations daily across companies building AI-native products.
Mem0 is a Y Combinator (S24) company, backed by top-tier investors including Peak XV and Basis Set Ventures. We raised $24M to make this the default memory infrastructure for AI.
The Founders
Deshraj Yadav, Co-founder and CTO. Led the AI Platform at Tesla Autopilot, enabling large-scale training, model evaluation, and observability for Tesla's full self-driving development. MS in CS from Georgia Tech (ML specialization). Created EvalAI as his master's thesis, an open-source ML evaluation platform used by researchers at CMU, Stanford, Facebook, and Google. Published at CVPR, ECCV, AAAI.
Taranjeet Singh, Co-founder and CEO. Started as a software engineer at Paytm, then built an AI-powered tutoring app at Gradeup (acquired by Byju's) that was featured at Google I/O. Joined Khatabook (YC S18) as first growth engineer and became Senior PM. Built cookup.ai, the first GPT app store, and scaled it to 1M+ users with zero marketing spend. Co-authored an O'Reilly book chapter on industrial NLP alongside researchers from Google AI, CMU, and Microsoft Research.
Together, Deshraj and Taranjeet co-created EvalAI and later built Embedchain, an open-source RAG framework with 2M+ downloads. While building Embedchain, they saw firsthand how LLMs forget everything between sessions, leading to repetitive, impersonal interactions. Mem0 was born to fix that: a hybrid memory architecture combining graph, vector, and key-value stores that makes AI applications stateful, personalized, and cost-efficient.
How We Work
Office-first in SF. Hallway chats, whiteboard sessions, and shared meals. The best ideas happen in person.
Velocity with craftsmanship. We ship fast but build for the long term. Every system needs to be fast, reliable, and elegant.
We debug retrieval quality over lunch. Half our Slack is embedding comparisons. If you've ever argued about chunk sizes at 11pm, you'll fit right in.
Data-driven, not ego-driven. The best solution wins, whether it comes from a founder or an engineer who joined yesterday. Results and metrics guide decisions.
Small team, big leverage. You'll work directly with the founders and a tight research + backend team. No layers, no committees.