# Backend Engineer

**Company:** [Mem0](https://hotfix.jobs/companies/mem0)
**Location:** Remote
**Role:** Backend Engineering
**Experience:** 5+ years
**Skills:** Python, REST APIs, FastAPI, Django, Flask, SQL, Postgres, MySQL, Neo4J, Amazon Neptune, AWS, Docker, Kubernetes, Redis, OpenTelemetry
**Posted:** 2026-08-21

> Build and operate the backend platform powering AI-agent memory, including REST APIs, relational and graph data models, Python services, and production infrastructure. The role requires 5+ years of backend experience, strong Python and SQL skills, and hands-on AWS, Docker, and Kubernetes expertise.

## Job Description

## Responsibilities
- Design and ship REST APIs, including contracts, versioning, authentication, rate limits, migrations, and documentation.
- Model data and schemas across relational and graph databases, enforcing integrity and performance.
- Debug customer issues end to end using logs, metrics, and traces; reproduce problems, ship fixes, and add preventative guardrails.
- Optimize SQL and service performance using query analysis, indexes, partitioning, pagination, and caching.
- Build Python services with asynchronous programming, web frameworks, background jobs, queues, and schedulers.
- Containerize and operate services with Docker, Kubernetes (EKS), and AWS services including EC2, RDS/Aurora, S3, and IAM.
- Instrument services with custom metrics, structured logging, tracing, SLOs, and alerts.
- Collaborate with frontend and research teams to scope APIs and deliver production features.

## Requirements
- 5+ years building backend systems and shipping REST APIs to production.
- Strong Python fundamentals, asynchronous programming experience, and experience with FastAPI, Django, or Flask.
- Strong data modeling and SQL skills, including query tuning and performance debugging with Postgres or MySQL.
- Experience with graph databases such as Neo4j or Amazon Neptune.
- Experience operating services on AWS with Docker and Kubernetes.
- Demonstrated root-cause analysis and ownership from incident through prevention.
- Clear communication and effective collaboration with frontend, research, and customers.

## Nice to Have
- GraphQL or gRPC.
- Event-driven systems such as SNS, SQS, or Kafka.
- Background workers such as Celery or RQ.
- Caching, rate limiting, multi-tenancy, and feature-flag strategies.
- Security and privacy best practices, including PII handling and secrets management.
- Deep observability experience with OpenTelemetry and SLO-based alerting.
- Search, retrieval, or memory systems experience.
- On-call experience and blameless postmortems.
- Early-stage startup, Series A, YC, or founding engineer experience.

## Compensation and Benefits
- No salary information provided.

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