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Senior Software Engineer (Database Infrastructure)

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Hybrid

Senior Software Engineer (Database Infrastructure)

Gusto

Senior Software Engineer (Database Infrastructure)

Skills

Ruby on RailsRubyPostgreSQLMySQLCockroachdbKafkaRedisAIKubernetes

2 months ago

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Important information


Contract type:

Permanent

Salary:

$222,000 – $245,000 / year

Location:

San Francisco, CA, USA

Work mode:

Hybrid

Published on:

13 August 2026

What they need


  • We’re looking for an experienced infrastructure engineer to help evolve how Gusto stores and accesses data as the company scales
  • You’ll help build a platform that lets engineering teams provision and access new datastores, evaluate and stand up highly available, horizontally scalable storage systems, and continue strengthening the resilience of the databases our product already depends on
  • This is a high-impact role shaping both the tools and the technology choices behind Gusto’s storage layer
  • The Datastores Infrastructure Engineering team designs, builds, and operates the data platforms that power Gusto’s product: Kafka, MySQL, Postgres, and Redis
  • As Gusto grows, we’re rethinking how the rest of engineering provisions and accesses storage — building self-service tooling for new datastores, exploring and adopting highly available, horizontally scalable systems, and continuing to reduce blast radius and improve the resilience of the databases we already operate
  • Build the tooling and platform that let engineering teams provision and access new datastores, and evaluate and pilot highly available, horizontally scalable storage systems to meet Gusto’s growing needs
  • Take ownership of Kafka, from capacity planning and partitioning through performance tuning and reliability at scale, and help stand up and operate new non-relational datastores like DynamoDB
  • Coordinate migrations and topology changes across the datastore platform (MySQL, Postgres, Redis, Kafka) with minimal disruption to production
  • Drive efficiency and reliability improvements across the platform through query and consumer optimization, caching strategies, and workload management, backed by strong automation and standards for data consistency, integrity, and security
  • Participate in on-call and drive long-term, sustainable reductions in operational burden
  • Partner with product engineering teams to enable rapid, reliable product development, and share knowledge to grow the team’s collective operating expertise

Benefits

  • Gender-affirming care and support
  • Family care and support, including family planning and fertility benefits
  • A variety of mental health resources
  • Medical, dental, and vision insurance for employees and dependents
  • Free meals and refreshments at the office (conversation and community is an added bonus!)
  • Paid vacation, sick time, bereavement, and holidays, paid leaves, sabbatical, and more- Strong communication skills, with the ability to simplify technical complexity and collaborate on technical direction across teams
  • Strong understanding of distributed systems fundamentals—partitioning, replication, consistency models, and failure modes—and proven experience coordinating migrations or topology changes in production with minimal disruption
  • Curiosity and ability to operate in an AI-native environment, using AI tooling to drive improvements in query optimization, performance evaluation, and infrastructure automation
  • Bonus: Experience working with Ruby on Rails or similar MVC frameworks at scale
  • Bonus: Experience with self-hosted distributed databases on Kubernetes (e.g., TiDB, CockroachDB, Vitess, or Citus), horizontal sharding, or service/vertical extraction from monolithic architectures
  • Experience running production infrastructure in the cloud, including caching systems like Redis/ValKey and streaming platforms like Kafka, with a track record of driving infrastructure optimization at scale
  • 6+ years of software engineering experience building and operating large-scale infrastructure systems, with deep hands-on expertise in streaming infrastructure (Kafka) and/or non-relational datastores (DynamoDB or similar) in production at scale

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