Deployed Engineer (Early Career- SF)

LangChain; San Francisco (CA); On-site; USD 160,000 - 175,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

Flexible vacation

401(k) plan

Meals on in-office days

Job summary

LangChain seeks a hands-on engineer to work with customers on the hardest AI problems, helping them adopt agent-based solutions and ship reliable agents into production. You will design POCs, guide evaluations, and deploy multi-step workflows using LangChain and related tools.

Join a highly technical team that collaborates across engineering, product, and go-to-market to deliver real-world impact while traveling to customer sites ~40% of the time.

Qualifications

• 1–3 years in software or customer engineering roles, ideally at a startup or high-growth company.
• Strong Python, JavaScript and systems fundamentals.
• Hands-on experience building and deploying agent-based/LLM-powered apps with multi-step workflows.
• Excellent technical communication and ability to translate AI concepts for customers.
• Willingness to work directly with customers during POCs, architecture reviews, and evaluations.

Responsibilities

• Co-architect and co-build production AI agents with customer teams and customers.
• Own the technical win in pre-sales by designing POCs and answering deep questions.
• Help deploy and operate agent-based applications (conversational, research, multi-step workflows).
• Advise on architecture, best practices, and roadmap-level decisions post-sale.
• Build and deliver tailored demos, trainings, and workshops for developers.
• Surface field feedback and contribute reusable patterns and example code.
• Collaborate with LangChain's engineering, product and design teams to guide direction.
• Occasionally contribute upstream code to improve outcomes.
• Travel about 40% to customer sites for deployment and onboarding.

Skills

Python

JavaScript

Systems fundamentals

Agent-based / LLM apps

Technical communication

POC & evaluations

Customer engagement

Tools

LangChain

LangGraph

AWS

GCP

Azure

Kubernetes

Job description

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.

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

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.

About The Role

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.

What You’ll Do

• 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

What You’ll Bring

• 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

Nice to Have’s:

• 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

Compensation

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

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