---
title: 'Deployed Engineer (Chicago) at LangChain'
canonical: 'https://feeny.ai/job/deployed-engineer-chicago-langchain-chicago-xy5eh85cx9hv'
type: 'job'
last_seen: '2026-09-10'
---

# Deployed Engineer (Chicago) at LangChain

- **Company:** [LangChain](https://feeny.ai/companies/langchain)
- **Location:** Chicago, IL
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-08-05
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.ashbyhq.com/langchain/38947013-3d0c-4257-aa58-ab8fe247ea3e

## 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. 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 Deployed Engineering 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

The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. This will be a hybrid in office role in Chicago, IL.

## What You’ll Do

- Co-architect and co-build production AI agents with customer engineering teams
- 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
- Run technical demos, trainings, and workshops for developer audiences
- Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers
- Occasionally contribute code upstream when it meaningfully improves customer outcomes
- Travel to customers up to 40% of the time

## What You’ll Bring

- 6+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up
- Strong Python, JavaScript and systems fundamentals
- Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling
- Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations
- Can explain technical tradeoffs clearly and build trust with developer audiences
- Take responsibility for outcomes, not just recommendations
- Have a bias toward action and enjoy figuring things out as you go
- Are excited about operating AI agents in production, not just building demos

## 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 basic Kubernetes concepts
- Have shipped and operated production software and are comfortable owning systems under real-world constraints

Compensation: Annual OTE range: $200,000–$250,000 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.

## About LangChain

## Company Overview
- **One-liner**: LangChain provides an agent engineering platform and open source frameworks that help developers build, evaluate, deploy, and operate reliable AI agents at scale.
- **Entity Type**: Private (Series B, unicorn)
- **Headquarters**: San Francisco, California, United States (with offices in New York, Boston, and Amsterdam)
- **Founded**: Early 2023
- **Founders**: Harrison Chase and Ankush Gola

## Core Business
- **Primary industry/industries**: Artificial Intelligence, Developer Tools, Agent Engineering
- **Target customers**: B2B – developers and engineering teams at enterprises (35% of Fortune 500 are customers) and startups
- **Mission or purpose statement**: “Make intelligent agents ubiquitous” – develop tools that make it easy to build reliable agents that can use data and take actions.

## Products & Services
- **[LangSmith](https://www.langchain.com/)**: Commercial agent engineering platform offering observability, evaluation (LLM-as-judge, human feedback), and deployment. Includes LangSmith Engine for automated issue detection and root cause analysis. Supports Python, TypeScript, Go, and Java SDKs.
- **[LangGraph](https://www.langchain.com/)**: Open source framework for building production agents with low-level control, durable checkpointing, and support for human-in-the-loop, multi-agent swarms, and A2A/MCP protocols.
- **[LangChain](https://www.langchain.com/)**: Original open source framework for building agents quickly with templates and any model provider.
- **[Deep Agents](https://www.langchain.com/)**: Agent harness for autonomous, long-horizon tasks with built-in memory and concurrency.
- **[Fleet](https://www.langchain.com/)**: No-code agent builder that lets non-technical users describe tasks in plain language; agents act across daily tools with enterprise security.

## Market Standing
- **Valuation/Market Cap**: $1.25 billion (unicorn status, per November 2025 Series B round)
- **Key Metric**: Total Funding – $160 million (Seed: $10M led by Benchmark; Series A: $25M led by Sequoia Capital; Series B: $125M led by IVP). Annual Revenue (LinkedIn estimate): $8.5 million.
- **Notable Investors/Partners**: IVP (lead Series B), Benchmark (lead Seed), Sequoia Capital (lead Series A). Customers include Zip, Vanta, Klarna, Workday, LinkedIn, Cloudflare.
- **Growth Signals**:
  - Headcount: 212 employees (+264.8% YoY, +9.9% monthly)
  - 1 billion+ monthly open source downloads
  - 1 billion+ events ingested per day on LangSmith
  - 35% of Fortune 10 are LangSmith customers
  - 6,000+ active LangSmith customers
  - Awards: Forbes AI 50, InfraRed 100, IA40, Enterprise Tech 30
  - Active job postings: 123 (monthly +4.2%, yearly +668.8%)

## Competitive Advantages
- **Open source ecosystem**: LangChain and LangGraph are the most popular open source frameworks for building LLM agents, with a massive community (100M+ monthly downloads) that drives adoption and talent.
- **Full lifecycle platform**: Covers building (open source frameworks), evaluating (LangSmith), deploying (agent server), and operating (LangSmith Engine) – a vertically integrated solution.
- **Framework-agnostic**: LangSmith works with any agent stack (OpenAI, Anthropic, etc.) via SDKs, reducing vendor lock-in.
- **Enterprise trust**: Already embedded in Fortune 500 companies; strong security and compliance features for production AI.

## Strategic Focus
- **Agent reliability**: Investing heavily in evaluation and observability to make agents “reliably good” – the hardest problem in production AI.
- **Long-horizon autonomy**: Deep Agents and Fleet target autonomous, multi-step tasks that require memory and human collaboration.
- **Global expansion**: Offices in US, Europe, and India; hiring across sales, engineering, and customer success to serve a growing international customer base.

## Why Work Here
- **Culture**: Fast-moving, open source–first startup with a mission to shape how the world uses AI. Described as hiring “the best in the business” with a focus on engineering excellence.
- **Work policy**: Hybrid/office presence in San Francisco, New York, Boston, and Amsterdam. Remote roles may exist (not explicitly stated, but global hiring suggests flexibility).
- **Notable perks/engineering culture**:
  - Work on cutting-edge agent technology used by millions of developers.
  - High autonomy and impact – small team with big ambitions.
  - Strong alumni network from top tech companies (AWS, Datadog, HashiCorp, GitLab, etc.).
  - Recent departures include VP of Marketing (Diana Smith, Mar 2026) – indicates some churn, but overall rapid hiring.
  - Active job postings across engineering, sales, product, and consulting – strong growth trajectory.

## Sources
1. [langchain.com](https://www.langchain.com/) – Official website (products, stats, customers)
2. [langchain.com/careers](https://www.langchain.com/careers) – Careers page (awards, values)
3. [langchain.com/about](https://www.langchain.com/about) – About page (mission, history, funding, team)
4. [linkedin.com/company/langchain](https://www.linkedin.com/company/langchain) – LinkedIn profile (headcount, revenue, funding rounds, job trends, talent sources)

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