Airbyte

Senior Software Engineer, Platform Fullstack - Hiring Sprint

Airbyte
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2 months ago

Base Salary

$196k - $255k/yr

Responsibilities

  • Design and build internal platform applications and product surfaces
  • Develop dashboards for deployments, infrastructure health, connector operations, and platform performance
  • Build user-facing features in Airbyte Cloud and Flex
  • Create self-service tools for infrastructure provisioning, service management, and production troubleshooting
  • Build React and TypeScript applications backed by scalable backend services
  • Design APIs and services for internal engineering workflows and customer-facing product features
  • Improve developer experience through automation, release workflows, deployment visibility, and operational dashboards
  • Improve performance, accessibility, reliability, and maintainability of user-facing product surfaces
  • Build interfaces and reporting that support observability, incident response, production operations, and system-health visibility
  • Reduce operational toil through automation and establish reusable platform components and engineering standards
  • Mentor engineers through design reviews, architecture discussions, and technical leadership
  • Help shape Airbyte’s platform and product engineering direction

Requirements

  • At least five years of experience building production full-stack applications
  • Deep expertise with React and TypeScript
  • Strong backend engineering experience building APIs and distributed systems
  • Experience shipping user-facing SaaS products alongside internal tools, developer platforms, or operational dashboards
  • Experience working with product managers and designers to ship customer-facing features
  • Familiarity with cloud infrastructure and modern deployment workflows
  • Strong product instincts and customer empathy for internal and external users
  • Excellent written and verbal communication skills
  • Experience with Kubernetes, Docker, Terraform, or cloud infrastructure is preferred
  • Experience with GitHub Actions, CI/CD pipelines, or developer productivity tooling is preferred
  • Familiarity with Grafana, Datadog, or Prometheus is preferred
  • Experience with Java or Kotlin is preferred
  • Experience with distributed systems, cloud-native architectures, internal engineering tools, developer platforms, data infrastructure, or large-scale SaaS platforms is preferred

Benefits

  • Flexible PTO with a culture encouraging at least 25 days off annually
  • 16 weeks of fully paid parental leave for all parents
  • Comprehensive medical, dental, and vision coverage for employees and dependents
  • 401(k) retirement plan
  • Professional development budget, conference sponsorship, and book reimbursement
  • Commuter benefits and monthly internet reimbursement
  • Breakfast and lunch in the San Francisco office
  • Onsite four days per week in San Francisco, California
  • Expedited engineering hiring sprint with an in-person onsite during the week of July 20

Tech Stack

AirbyteDatadogDockerGitHub ActionsGrafanaJavaKotlinKubernetesPrometheusPythonReactTerraformTypeScript
Airbyte

About Airbyte

51-200 employees

Founded in 2020, Airbyte is the context layer for production-grade AI agents. AI agents fail in production for one reason: they can't see the business. They make scattered API calls at runtime, burn tokens reconciling fragmented data, and break under real workloads. Airbyte solves this by giving agents unified, permission-aware access to the operational data scattered across the tools companies actually run on (CRM, billing, support, product, internal systems) through a hybrid architecture that combines large-scale replication (for cross-system search and discovery) with real-time fetching (for fresh operational state). It's the combination production agents actually need, built on the connector footprint we've hardened over six years. We've raised $181M from Benchmark, Accel, Altimeter, Coatue, Y Combinator, and others. Today, 25,000+ companies sync data with Airbyte's 600+ connectors. Open source remains core to how we build, because the data foundation under your AI agents is too important to be a black box.