Software Engineering Manager, AI Observability & Evals Platform

Langchain, Inc
New York, NY, United States
2 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$200,000.0 - $250,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Databases Programming Tools Python (Programming Language) PostgreSQL Redis TypeScript ReactJS Large Language Models Build Management Vertica

Job description

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., * 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

Requirements

  • 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

Benefits & conditions

We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations., Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

About the company

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. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.

With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.

Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:21 min

Exploring the target application for front end tests

Anna Mcdougall · JS Congress

3:55 min

Demonstrating semantic routing thresholds with the Redis vector library

3:25 min

Constructing scalable AI solutions using LangChain and LangGraph

Julián Duque Julián Duque · World Congress 2025

2:59 min

Introduction and transitioning into the tech industry

Anna Mcdougall · JS Congress

3:42 min

Comparing in-memory and Redis storage for cache scalability

Simone Sanfratello · World Congress 2022

2:16 min

Writing foundational applications with LangChain expression language

Julián Duque Julián Duque · World Congress 2025

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