Research Engineer, LangSmith Engine
- Salary
- $240,000 - $280,000
- Level
- Mid
- Work type
- On-site · New York
Not stated in the posting: visa.
Open. First seen 9 September 2026.
About the role
About Us
LangChain's standard text
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.
LangChain's standard text
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 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.
About the Role:
We’re looking for an experienced research engineer to help make the Engine agent more capable and more efficient.
You’ll study real agent failures, build benchmarks that capture what matters, run experiments to improve performance, and turn successful ideas into production. 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.
This role also requires a understanding of production engineering and system-level tradeoffs. Engine is a production system, so improving an agent is not just about maximizing benchmark performance—it also means understanding the impact on cost, latency, reliability, and scalability. You’ll work in the same team with production engineers to design, test, and ship improvements that work reliably in real-world environments.
Location: SF and NYC
What You’ll Do:
- 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.
- Turn successful experiments into production improvements, working closely with engineers and researchers to measure impact and prevent regressions.
- Help define the ML roadmap and technical direction for improving Engine agents, and mentor other engineers through strong technical leadership.
What You’ll Bring:
- 4+ years of experience in ML/AI research, or a closely related field.
- Master’s or Ph.D. in a relevant scientific field.
- Hands-on experience working with LLMs and AI agents, including analyzing model behavior and improving real-world performance
- Strong experience designing benchmarks, evaluations, and experiments for AI/ML systems; you know how to tell whether a change actually made an agent better.
- Strong software engineering skills, with a track record of taking ideas from research prototype to measurable production impact.
- You have maximum agency and strong research judgment: you can identify high-impact problems, work through ambiguity, move quickly, and communicate your findings clearly.
Nice to Have:
- Ph.D. in Machine Learning, Computer Science or Physics.
- Hands on experience with LLM-as-a-judge, automated graders, synthetic data generation, or human evaluation.
- Hands on experience with reinforcement learning, preference optimization, SFT, RLHF/RLAIF, or other post-training techniques for LLMs.
- Experience optimizing LLM agents for cost, latency, or task efficiency on productions
- Experience with model serving, inference optimization, distributed systems, or GPU infrastructure.
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. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. 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.
What this role asks for
In most of LangChain's ads
Cloudflare · LLM
Named in most of its open postings, whatever the role.
82% of this description is written for the role. The rest is LangChain's standard text, folded away below.
Read against LangChain's other open postings on this site.
The team: Engineering HIRES STEADILY
This role is one of 26 open in Engineering. 7 were posted in the last 30 days and the oldest in February: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
Cloudflare (26 of 26), LangChain (26 of 26), LLM (17 of 26), Python (16 of 26), TypeScript (13 of 26), Golang (11 of 26), PostgreSQL (11 of 26)
OTHER ROLES ON THIS TEAM
- FullStack Engineer, AI Observability & Evals Platform (LangSmith) posted Oct 14
- Senior Fullstack Software Engineer, AI Observability & Evals Platform (NY) posted Oct 8
- Senior Backend Software Engineer, AI Observability & Evals Platform (NYC) posted Oct 8
- Analytics Engineer posted Oct 5
- Software Engineering Manager, Database (SmithDB) posted Oct 5
- IT Systems Administrator posted Oct 5
- Senior Frontend Engineer, AI Observabilty Platform posted Sep 24
- Senior Fullstack Engineer, AI Observability & Evals Platform posted Sep 12
- Senior Backend Software Engineer, AI Observability & Evals Platform (LangSmith) posted Sep 12
- Software Engineering Manager, AI Observability & Evals Platform posted Sep 11
- Developer Productivity posted Sep 10
- Software Engineer, Agent Systems (GTM Engineering) posted Sep 6
- Senior Frontend Platform Engineer, Design Systems posted Aug 22
- Security Engineer - Detection & Response posted Aug 17
- Senior Frontend Engineer, AI Observability & Evals Platform posted Aug 13
- Frontend Engineer, AI Observability & Evals Platform posted Aug 12
- Product Designer posted Jul 23
- IT Systems Engineer posted Jul 10
- Senior Product Engineer - Growth & Monetization posted Jun 10
- Senior Software Engineer, Database (SmithDB) posted May 13
- GTM Engineer posted Apr 29
- GTM Engineer posted Feb 15
- Senior Backend Software Engineer, AI Observability & Evals Platform (SF) posted Jan 8
- Senior Fullstack Engineer, AI Observability & Evals Platform (SF) posted Feb 19
- Python OSS Engineer posted Feb 10
From the team and dates on LangChain's own job board.
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