FullStack Engineer, AI Observability & Evals Platform (LangSmith)

LangChain•Cambridge, MA
•$145,000 - $180,000

About The Position

LangChain is hiring a Fullstack Engineer to work on LangSmith, its commercial AI observability and evaluations platform. The role involves building new platform features and functionality while working closely with enterprise customers, developer end-users, and internal stakeholders. The engineer will work across Go, Python, and TypeScript, partnering with product and design teams to iterate on features and contribute to the product roadmap. The role calls for delivering on aggressive project timelines while maintaining high engineering standards through clean, maintainable, well-tested code.

Requirements

  • At least 2 years of software engineering experience working on complex platform products.
  • Fullstack engineering experience with Go or Python on the backend and React and TypeScript on the frontend.
  • Solid understanding of database systems, particularly Postgres and Redis.
  • Experience designing and scaling APIs, preferably for high-performance, data-intensive applications.
  • Strong ownership and a get-stuff-done mindset, with comfort shipping quickly and iterating based on user feedback.
  • Strong communication skills and the ability to collaborate with internal stakeholders and engage directly with customers.

Nice To Haves

  • Experience with AI/LLM-powered applications, developer tools, or observability platforms.

Responsibilities

  • Develop and implement product features across the Go, Python, and TypeScript stack.
  • Collaborate with product and design teams to iterate on features and enhance the product roadmap.
  • Deliver against aggressive project timelines while maintaining high engineering standards and writing clean, maintainable, well-tested code.
  • Work closely with enterprise customers, developer end-users, and internal stakeholders.

Benefits

  • Medical coverage
  • Dental coverage
  • Vision coverage
  • Flexible vacation
  • 401(k) plan
  • Meals on in-office days in the US
  • Meaningful equity
  • Variable compensation for relevant roles
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