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.
This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on.
This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite.
Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.
You'll work on some of the hardest problems in applied AI alongside customers. You will help customers adopt innovative new practices in agentic engineering, and ensure they ship reliable agents into production, quickly. The feedback loop is fast, the impact is visible, and your work directly shapes how AI agents are built in the real world.
Co-architect and co-build production AI agents with customer engineering teams and customers
Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations
Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows
Advise customers post-sale on architecture, best practices, and roadmap-level decisions
Build and run tailored demos, trainings, and workshops for developer audiences
Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers
Interface with LangChain's engineering, product and design (EPD) team to share field perspectives and guide product direction based on customer priorities
Occasionally contribute code upstream when it meaningfully improves customer outcomes
This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement
1-3 years of experience in software engineering, customer engineering, solutions engineering, founding engineering, or a similarly technical role, ideally at a startup or high-growth company
Strong Python, JavaScript and systems fundamentals
Hands-on experience building and deploying agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling
Strong technical communication skills and builder credibility; Can explain technical tradeoffs clearly, translate complex AI concepts into actionable insights, and build trust with technical customers and engineering teams
Excited to work directly with customers during POCs, architecture reviews, and technical evaluations
Take responsibility for outcomes, not just recommendations
Have a bias toward action and enjoy figuring things out as you go
Are excited about shipping AI agents in production
You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks
Worked with LLM evaluation, observability, or guardrails
Have experience with cloud environments (AWS, GCP, Azure), containers, and Kubernetes concepts
Have shipped and operated production software and are comfortable owning systems under real-world constraints
Annual OTE range: $160,000-175,000 USD
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 include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
Job details are sourced from the employer's original posting.
Open job postingAbout the company
LangChain is building the agent engineering platform that makes intelligent agents ubiquitous. Their open source frameworks, LangChain and LangGraph, see over 90+ million downloads per month and help developers build agents with speed and granular control. LangSmith offers observability, evaluation, and deployment for rapid iteration, enabling teams to transform LLM systems into dependable products.