Performance Engineer

About the opportunity

About Supabase Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. About the Role We're hiring experienced performance engineers to find and land performance wins across the Supabase stack — from the query optimiser to block device level, and across the network paths and cloud infrastructure that connect our distributed platform. This is a performance delivery role: real, measured improvements to our database, platform, and APIs as we scale toward enterprise and platform-grade workloads. The methodologies you develop and tooling you build exist to multiply that delivery. You'd join a new performance team as one of its first members, working alongside a deeply seasoned performance engineer, with the team growing to roughly six this year. There's no legacy process to inherit — you'll help define how performance engineering works at Supabase. What you'll do Find bottlenecks in live production systems and characterize them precisely enough that the owning team can act on them without you in the room. Partner closely with database teams (e.g. Multigres, OrioleDB) and infra teams to land concrete performance improvements. Build, communicate, and evolve performance methodologies and tooling that turn live production data into actionable insight. Partner with the observability team to capture the right signals and establish a unified view of platform performance (latency, throughput, tail behavior) across products. Help teams self-serve performance analysis and make performance a first-class engineering concern. Problems you might work on Tune the kernel's paging behavior to production workloads Reduce memory overhead in OrioleDB and Multigres Identify and eliminate sources of latency spikes from application to kernel level Identify scalability bottlenecks across the entire stack and work the appropriate teams in Supabase and the wider community to resolve them What we're looking for Deep experience in performance engineering, specifically performance analysis of complex distributed systems. You can walk the whole stack: follow a tail-latency problem from the query optimizer through the syscall boundary to the IO scheduler — or across pooler hops, network paths, and availability zones — reading profiles and traces at every layer. Depth on at least one end of that stack: Linux kernel internals (virtual memory, scheduling, networking, IO) or database internals (query planning, storage engines, buffer and WAL management) Strong working knowledge of networking and cloud infrastructure performance: TCP behavior under load, network virtualization overhead, and the performance characteristics of AWS primitives (EBS throughput and IOPS, instance network limits, placement groups, cross-AZ latency). Proven ability to turn performance insights into real product and architecture improvements — including getting teams you don't belong to to prioritize and ship the fix. Strong written communication: your problem characterisations are precise, reproducible, and compelling on their own. Pragmatic, tooling-oriented mindset; comfort working across product, infra, and database teams. What We Offer Fully Remote We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world. ESOP Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together. Tech Allowance Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work. Health Benefits Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us. Annual Off-Sites Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year. Flexible Work We operate asynchronously and trust you to manage your own time. You know what needs to be done and when. Professional Development Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth. About the Team Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love. ~400 team members 60+ countries 20+ languages spoken Over $1B raised (including our $500M Series F) 540,000+ community members We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.

Responsibilities

• Find bottlenecks in live production systems and characterize them precisely enough that the owning team can act on them without you in the room.
• Partner closely with database teams (e.
• Multigres, OrioleDB) and infra teams to land concrete performance improvements.
• Build, communicate, and evolve performance methodologies and tooling that turn live production data into actionable insight.
• Partner with the observability team to capture the right signals and establish a unified view of platform performance (latency, throughput, tail behavior) across products.
• Help teams self-serve performance analysis and make performance a first-class engineering concern.
• Problems you might work on Tune the kernel's paging behavior to production workloads Reduce memory overhead in OrioleDB and Multigres Identify and eliminate sources of latency spikes from application to kernel level Identify scalability bottlenecks across the entire stack and work the appropriate teams in Supabase and the wider community to resolve them What we're looking for Deep experience in performance engineering, specifically performance analysis of complex distributed systems.
• You can walk the whole stack: follow a tail-latency problem from the query optimizer through the syscall boundary to the IO scheduler — or across pooler hops, network paths, and availability zones — reading profiles and traces at every layer.