LangChain

LangChain

Research Engineer, LangSmith Engine

New York, NY · Mid

Sponsorship not specified$240k-$280kDetected 63 days ago
Distributed SystemsMachine LearningLLMsAgentic AILangGraphHRISResearchLeadershipCommunication

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odds of building a lasting career here

61Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

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Files H-1B transfers

9 transfer filings in the last year, covering 9 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

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About the role

  • We're looking for an experienced research engineer to help make the Engine agent more capable and more efficient.
  • This may include prompting and agent-harness improvements, model selection, fine-tuning and post-training custom models.
  • The focus is on measurable improvements to the overall agent.

Responsibilities

  • Build and maintain benchmarks and evaluations that measure the quality and efficiency of Engine agents on real-world tasks.
  • Design and run experiments to improve agent performance across models, prompting, context, tools, orchestration, and agent strategies.
  • Explore and implement post-training and fine-tuning techniques when they can meaningfully improve agent capabilities, quality, or cost.
  • You'll study real agent failures, build benchmarks that capture what matters, run experiments to improve performance, and turn successful ideas into production.
  • You'll work in the same team with production engineers to design, test, and ship improvements that work reliably in real-world environments.

Requirements

  • 4+ years of experience in ML/AI research, or a closely related field.
  • You have maximum agency and strong research judgment: you can identify high-impact problems, work through ambiguity, move quickly, and communicate your findings clearly.
  • Strong experience designing benchmarks, evaluations, and experiments for AI/ML systems
  • you know how to tell whether a change actually made an agent better.

Nice to have

  • Hands on experience with LLM-as-a-judge, automated graders, synthetic data generation, or human evaluation.
  • Experience optimizing LLM agents for cost, latency, or task efficiency on productions
  • Experience with model serving, inference optimization, distributed systems, or GPU infrastructure.

Skills

  • Strong software engineering skills, with a track record of taking ideas from research prototype to measurable production impact.

Compensation

  • Salary Range: $240,000-$280,000 USD
  • Compensation Philosophy:
  • We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks.
  • We are hiring for this role across a range of scope, and the compensation band reflects that.

Benefits

  • Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
  • Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.

Company info

  • 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.
  • The LangSmith Engine team is building a proactive agent engineer that analyzes production traces, identifies important failures, recommends and writes fixes, and helps prevent those issues from coming back.
  • We're building agents that can understand complex software systems and continuously improve the quality of other AI agents.
  • 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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This listing is sourced directly from LangChain's careers page and normalized into a canonical job model.