Senior Backend Software Engineer, AI Observability & Evals Platform (NYC)

Posted 17 Hours Ago
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New York, NY, USA
In-Office
180K-240K Annually
Senior level
Information Technology • Software • Database
The Role
Build and maintain backend services and APIs powering LangSmith’s observability and evaluation platform. Responsibilities include architectural design, storage and query optimization, reliability engineering, testing, monitoring, alerting, production troubleshooting, root-cause analysis, technical documentation, and cross-functional feature delivery. The role focuses on high-throughput, mission-critical AI platform systems.
Summary Generated by Built In
About Us

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.

About The Team

The LangSmith team owns and builds LangChain's core platform for observability, evaluation, and production reliability of AI systems. From tracing and annotation to run rules, evaluations, and beyond, this team owns LangSmith end-to-end. If you want to define what great AI observability looks like at production scale, this is where that work gets done.

 
About The Role

We are looking for a Senior Backend Engineer to join us. In this role you will be building the backend systems that power LangChain’s observability and evals platform. You will work on the core services that allow developers to monitor and evaluate their AI applications at scale. While the focus is on backend feature development, familiarity with fullstack or frontend engineering, performance tuning, and debugging production issues would be extremely valuable.

 
What You'll Do
  • Design, develop, and maintain backend services and APIs to support LangSmith’s tracing, monitoring, and evaluation workflows.

  • Collaborate on architectural decisions to ensure systems are performant and maintainable.

  • Optimize storage and query performance for high-volume observability and evaluation data.

  • Ensure system reliability through strong testing, monitoring, and alerting practices.

  • Troubleshoot and resolve production issues, performing root-cause analysis and implementing long-term fixes.

  • Create and maintain technical documentation, including system design and API references.

  • Work closely with full-stack engineers, product managers, and product designers on rolling out new features.

     
What You'll Bring
  • 5+ years of professional experience in backend engineering working on highly complex products

  • Proficiency in one or more backend languages/frameworks, ideally Python or Go

  • Strong understanding of API design and building reliable data services.

  • Experience with high-throughput or mission-critical systems.

  • Demonstrated ability to optimize backend services for performance and reliability.

  • Experience with database systems (Postgres, Redis, Clickhouse), and cloud platforms (AWS, GCP, Azure)

  • Strong communication skills, with the ability to collaborate cross-functionally

  • Customer centricity and ownership mentality

     

Compensation

Annual salary range: $180,000- $240,000

Compensation Philosophy:

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

Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Skills Required

  • 5+ years of professional backend engineering experience working on highly complex products
  • Proficiency in one or more backend languages or frameworks, ideally Python or Go
  • Strong understanding of API design and building reliable data services
  • Experience with high-throughput or mission-critical systems
  • Demonstrated ability to optimize backend services for performance and reliability
  • Experience with database systems including Postgres, Redis, and ClickHouse
  • Experience with cloud platforms including AWS, GCP, or Azure
  • Strong communication skills and ability to collaborate cross-functionally
  • Customer centricity and ownership mentality
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The Company
HQ: San Francisco, CA
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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