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Developer Productivity

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Developer Productivity in USA

  • LangChain
  • Full time
  • Email
  • San Francisco, CA

Responsibilities

  • Own end-to-end test strategy across APIs, services, UI, data, and infrastructure.
  • Build ephemeral Kubernetes environments for pull requests and release candidates, seed test data, and run hermetic test suites.
  • Improve GitHub Actions pipelines through parallelization, caching, deterministic seeds, flake tracking, and quality gates.
  • Add observability to testing workflows with logs, traces, dashboards, and rich failure artifacts.
  • Establish performance and reliability baselines, including SLIs, SLOs, and regression detection.
  • Support incident workflows by reproducing issues, adding regression tests, and improving runbooks and postmortems.
  • Write test plans, playbooks, contributor guidelines, and other testing documentation.

Requirements

  • 3+ years of experience as a software engineer or infrastructure engineer.
  • Strong hands-on experience with Python and testing frameworks such as pytest.
  • Experience with CI/CD systems, preferably GitHub Actions, and improving pipeline performance and reliability.
  • Solid understanding of API testing, mocking or stubbing, and data setup and teardown.
  • Ability to define quality standards, write test plans, and drive cross-team execution.
  • Preferred experience with k6 or other load and performance testing tools; Datadog or OpenTelemetry; Kubernetes and containerized environments; Helm, Terraform, Kubernetes networking, or secrets management; SQL and databases such as Postgres, ClickHouse, or BigQuery; and Go, Node, or React.

Benefits

  • Medical, dental, and vision coverage.
  • Flexible vacation.
  • 401(k) plan.
  • Meals on in-office days in the US.
  • In-person work five days per week in San Francisco, CA or New York, NY.

Salary: $175k - $240k/yr

LangChain

At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. What began as widely adopted open-source tools has grown into a platfo...

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