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

LangChain · Boston, MA

Location
Boston, MA
Employment
Full time
Level
Senior
Posted
Today

About this role

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

This role is based onsite in Boston, MA.


We are looking for a Senior Backend Engineer to join our growing engineering team in Boston. In this role you will be building the backend systems that power LangSmith, LangChain’s observability and evals platform. You will work on the core services that allow our customer's developer teams 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 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:

  • 4+ years of professional experience in backend engineering working on highly complex products

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

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

  • Experience with high-throughput, 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) would be a bonus.

  • 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.

As published by LangChain. Applications are handled on their site.

About LangChain

Making it easy to develop LLM applications from prototyping to production

All 109 openings at LangChain

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Apply to LangChain with a resume written for this role.

Queue Senior Backend Software Engineer, AI Observability & Evals Platform (LangSmith) and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in LangChain’s form for you.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

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  3. 03Each one is written up

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Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

  3. 03Each one is written up

    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

  • New matches ranked and written before you are up.
  • Every bullet stays inside what your history supports. Nothing invented.
  • Queued, submitted, interviewing, offer: one screen, not a spreadsheet.

500 free credits on sign-up. No card. Nothing is sent until you say so.

Listed from the job board LangChain publishes. Refolk is not the employer and does not handle their hiring. Applications go to LangChain directly.