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Staff Distributed Systems Engineer

Fomo

New York, NYJobPosted 1w agoStill listed 1w ago

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At a glance

Compensation
No compensation found
Location
New York, NY
Work Authorization
Not specified

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Job overview

Fomo seeks a Staff Distributed Systems Engineer to own reliability, scalability, and performance of its multi‑region backend platform, designing and operating high‑throughput services, improving datastore and cache systems, and implementing failover and disaster‑recovery capabilities for a trading application.

Skills & qualifications

RequiredNice to have

Skills

Reliability EngineeringScalabilityDisaster Recovery SolutionRedisNode.JsData SystemReliabilityApache KafkaDatadogPostgreSQLAWSTerraformGoTypeScriptNATS JetStreamKafkaAWS Performance InsightsHigh‑Throughput SystemsDisaster RecoveryObservability

Qualifications

8+ Years Backend Engineering Experience

Full job description

About the role fomo is a trading app for the rest of us. With fomo you can sign up in seconds and have instant access to any asset on-chain without the need for external wallets, bridges or prior knowledge. fomo has social features that are actually useful - follow top traders (with full access to their portfolio and trades) and find tokens early. fomo does all of this while providing the best-in-class execution and data for experienced traders. https://x.com/fomo

About the role

We are looking for a Staff Distributed Systems Engineer to own the reliability, scalability, and performance of our multi-region backend platform. You will own critical shared infrastructure, including datastores, caches, messaging systems, and regional application services, and design systems that remain predictable during traffic surges, dependency failures, infrastructure changes, and partial regional outages. You will also establish new failover and disaster-recovery capabilities within our stack, including defining recovery objectives and implementing the systems and testing required to recover services and data safely. This is a hands-on engineering role with direct ownership of production systems. You will build and operate application and infrastructure components while improving data systems and observability.

Responsibilities

  • Design and operate high-throughput, multi-region services.

  • Improve datastore and cache performance, capacity, replication, and failure handling.

  • Implement backpressure, concurrency limits, load shedding, rate limiting, circuit breakers, and bounded retries.

  • Reduce cross-region latency and improve data locality.

  • Design and test service, datastore, and regional failover procedures.

  • Help architect new features to operate at scale from day one.

  • Level-up the team on how to think about scale.

Qualifications

  • 8 or more years of backend, platform, or infrastructure engineering experience, or equivalent practical experience.

  • Experience designing and debugging distributed, high-throughput production systems.

  • Strong PostgreSQL experience, including query performance, indexing, connection pooling, replication, transaction contention, and failure modes.

  • Strong experience with Redis-compatible systems such as Redis, Valkey, Dragonfly, or KeyDB, including sharding, replication, memory management, hot keys, and failure handling.

  • Experience operating services on AWS, ideally using ECS, RDS, and ElastiCache.

  • Experience with infrastructure as code, preferably Terraform.

  • Proficiency in Go, TypeScript/Node.js, or a comparable systems-oriented language.

  • Hands-on experience designing and testing failover and disaster-recovery systems, including backup restoration, replication, regional failover, and RTO/RPO validation.

Nice to have

  • Experience with NATS JetStream, Kafka, or another durable messaging system.

  • Familiarity with Datadog APM and AWS Performance Insights.

  • Experience performing live datastore or cache topology migrations.

  • Experience operating systems with bursty or unpredictable traffic.

  • Experience with financial, trading, cryptocurrency, gaming, or other high-throughput systems.

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