Software Engineering Manager, Observability & Evals Platform

Reposted 7 Days Ago
Be an Early Applicant
San Francisco, CA
In-Office
200K-235K Annually
Senior level
Information Technology • Software • Database
The Role
Lead the architecture and implementation of product features, manage a team, and collaborate with stakeholders while ensuring high engineering standards.
Summary Generated by Built In

About the LangChain:

At LangChain, our mission is to make intelligent agents ubiquitous. We provide the agent engineering platform and open source frameworks developers need to ship reliable agents fast.

Our open source frameworks, LangChain and LangGraph, see over 90+ million downloads per month and help developers build agents with speed and granular control. LangSmith offers observability, evaluation, and deployment for rapid iteration, enabling teams to transform LLM systems into dependable production experiences.

LangChain is trusted by millions of developers worldwide and powers AI teams at companies like Replit, Clay, Cloudflare, Harvey, Rippling, Vanta, Workday, and more.

About the role:

We’re looking for an Engineering Manager to lead the team building LangSmith, our observability and evaluation platform for LLM applications. You’ll define the technical direction, grow and mentor a world-class engineering team, and partner with product and design to deliver features that help developers build and deploy trustworthy AI systems with confidence.

What you will do:

  • Build, mentor, and grow a high-performing team of engineers, fostering collaboration, ownership, and accountability

  • Strengthen LangChain’s engineering culture through mentorship, high-quality code, and technical excellence

  • Shape long-term technical direction and ensure scalability and reliability of LangSmith AI Observability Platform

  • Partner with product and design teams to define scope, sequence, and success criteria for key initiatives

  • Maintain a high bar for technical excellence while making sure the team moves with urgency and focus

  • Lead by example in writing clean, maintainable, and well-tested code in Go/Python and Typescript

  • Engage directly with customers to understand their needs and translate them into actionable product improvements

How to be successful in this role:

  • Experience managing or tech-leading teams delivering complex full-stack products

  • Strong technical background in Go/Python and React/Typescript

  • Solid understanding of databases (Postgres, Redis and ClickHouse)

  • Proven ability to design high throughput data-intensive systems

  • Bias towards shipping quickly and learning from customers

  • Strong communication skills—able to collaborate with internal stakeholders and engage directly with customers

  • Bonus: Experience building AI/LLM-powered applications, developer tools, or observability platforms

Compensation & Benefits

  • We offer competitive compensation that includes base salary, meaningful equity, and benefits such as health and dental coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation will vary based on role, level, and location. For team members in the EU and UK, we provide locally competitive benefits aligned with regional norms and regulations.

  • Annual salary range: $200,000- $250,000

Top Skills

APIs
Go
Postgres
Python
React
Redis
Typescript
Am I A Good Fit?
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The Company
123 Employees

What We Do

LangChain is the platform for building reliable agents. Our products power top engineering teams — from fast-growing startups like Lovable, Mercor, and Clay to global brands including AT&T, Home Depot, and Klarna.

LangGraph is a low-level orchestration framework for building controllable agents and long-running workflows. It’s used in production by teams at Replit, Uber, LinkedIn, GitLab, and more.

LangSmith offers unified evaluation and monitoring to help developers debug, evaluate, and improve their agents at scale.

LangChain provides hundreds of integrations and composable components, making it easy to connect with the latest models, tools, and databases — with minimal engineering overhead.

Together, these tools help teams build, deploy, and manage enterprise-grade agents, faster.

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