Mem0
Overview
Senior Infrastructure Engineer at Mem0. You will own the infrastructure that makes personalized AI possible at scale. This is deep technical work—profiling systems, rewriting queries, building monitoring, and ensuring our infrastructure can handle exponential growth. You will work directly with our founding team with significant autonomy to solve hard performance problems. When you ship code, millions of AI interactions depend on it working flawlessly. What you'll do
Optimize retrieval performance: Profile and rewrite database queries across our multi-store architecture to achieve
Scale infrastructure systems: Design and implement auto-scaling, connection pooling, and distributed caching to handle exponential growth Build end-to-end monitoring & alerting: Instrument the entire stack with detailed observability to maintain 99.99% uptime Design disaster-recoverable, multi-AZ systems: Implement robust failover mechanisms and geographic redundancy for mission-critical memory operations Debug production issues: On-call rotation to investigate and resolve infrastructure problems in real-time Implement reliability improvements: Build circuit breakers, retry logic, graceful degradation for mission-critical memory operations Optimize data pipelines: Improve memory ingestion, processing, and retrieval workflows for efficiency and accuracy You may be a good fit if you
5+ years hands-on backend/infrastructure engineering experience Deep database expertise: Production experience optimizing PostgreSQL, Redis, or graph databases (Neo4j preferred) Performance tuning mastery: Proven track record of 10x performance improvements (link to talk or PR a plus) Production scaling experience: Built systems handling millions of requests/day with strict latency requirements Infrastructure automation: Hands-on experience with Kubernetes, Terraform, CI/CD pipelines Monitoring & observability: Experience with APM tools, metrics, logging, alerting systems Startup mentality: Thrives in ambiguity; defaults to action Strong candidates may also have
Built or optimized vector databases, embedding systems, or ML infrastructure Experience with sub-100ms latency requirements (trading firms, gaming, real-time systems) Background at infrastructure companies (Redis, MongoDB, Databricks, etc.) Open source contributions to performance-critical projects Experience debugging with perf, flamegraphs, or distributed tracing Compensation & benefits
Base pay range: $165,000/yr - $195,000/yr Relocation and immigration support offered. We welcome engineers from non-traditional backgrounds and under-represented groups. If the mission excites you, please apply. Additional details
About Mem0: We are building the memory layer for AI agents. We’re backed by top-tier investors and are well capitalized. The hard problem: maintaining sub-100ms p99 latency while scaling exponentially. Seniority level
Mid-Senior level Employment type
Full-time Job function
Information Technology Industries
Technology, Information and Internet
#J-18808-Ljbffr
Senior Infrastructure Engineer at Mem0. You will own the infrastructure that makes personalized AI possible at scale. This is deep technical work—profiling systems, rewriting queries, building monitoring, and ensuring our infrastructure can handle exponential growth. You will work directly with our founding team with significant autonomy to solve hard performance problems. When you ship code, millions of AI interactions depend on it working flawlessly. What you'll do
Optimize retrieval performance: Profile and rewrite database queries across our multi-store architecture to achieve
Scale infrastructure systems: Design and implement auto-scaling, connection pooling, and distributed caching to handle exponential growth Build end-to-end monitoring & alerting: Instrument the entire stack with detailed observability to maintain 99.99% uptime Design disaster-recoverable, multi-AZ systems: Implement robust failover mechanisms and geographic redundancy for mission-critical memory operations Debug production issues: On-call rotation to investigate and resolve infrastructure problems in real-time Implement reliability improvements: Build circuit breakers, retry logic, graceful degradation for mission-critical memory operations Optimize data pipelines: Improve memory ingestion, processing, and retrieval workflows for efficiency and accuracy You may be a good fit if you
5+ years hands-on backend/infrastructure engineering experience Deep database expertise: Production experience optimizing PostgreSQL, Redis, or graph databases (Neo4j preferred) Performance tuning mastery: Proven track record of 10x performance improvements (link to talk or PR a plus) Production scaling experience: Built systems handling millions of requests/day with strict latency requirements Infrastructure automation: Hands-on experience with Kubernetes, Terraform, CI/CD pipelines Monitoring & observability: Experience with APM tools, metrics, logging, alerting systems Startup mentality: Thrives in ambiguity; defaults to action Strong candidates may also have
Built or optimized vector databases, embedding systems, or ML infrastructure Experience with sub-100ms latency requirements (trading firms, gaming, real-time systems) Background at infrastructure companies (Redis, MongoDB, Databricks, etc.) Open source contributions to performance-critical projects Experience debugging with perf, flamegraphs, or distributed tracing Compensation & benefits
Base pay range: $165,000/yr - $195,000/yr Relocation and immigration support offered. We welcome engineers from non-traditional backgrounds and under-represented groups. If the mission excites you, please apply. Additional details
About Mem0: We are building the memory layer for AI agents. We’re backed by top-tier investors and are well capitalized. The hard problem: maintaining sub-100ms p99 latency while scaling exponentially. Seniority level
Mid-Senior level Employment type
Full-time Job function
Information Technology Industries
Technology, Information and Internet
#J-18808-Ljbffr