---
title: 'Fullstack Software Engineer, Applied AI at LangChain'
canonical: 'https://feeny.ai/job/fullstack-software-engineer-applied-ai-langchain-san-francisco-e33qg1va8ddd'
type: 'job'
last_seen: '2026-09-10'
---

# Fullstack Software Engineer, Applied AI at LangChain

- **Company:** [LangChain](https://feeny.ai/companies/langchain)
- **Location:** San Francisco, CA
- **Compensation:** $165k–$190k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2025-09-12
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.ashbyhq.com/langchain/c75915ba-a32b-4e17-873d-19b47564170d/application

**Skills:** Python, TypeScript, LLM systems, Prompting, Retrieval, Orchestration, Inference APIs, Model selection, AI evaluation systems, Monitoring systems, LangChain, LangGraph, Open source contribution

> Design, build, and deploy production-grade AI agents and workflows to transform internal operations and customer-facing products. The role involves developing agent architectures, evaluation pipelines, and integrating with cross-functional teams to drive automation and measurable business impact.

## 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 Applied AI team builds the agents that show the world what's possible with LangChain. We ship open source reference agents like Open SWE, Open Canvas, and our Deep Research agent that developers across the community use as starting points for their own production systems, while also building internal agents that power LangChain's own GTM and engineering workflows. It's a small, fast-moving team that operates at the frontier, iterating rapidly, running rigorous evals on our own work, and feeding hard-won learnings back into the platform. If you want to work on the frontier of agent-building, this may be the team for you.

## About The Role

We’re hiring fullstack Applied AI Engineers to help us build AI agents that power every part of LangChain from Marketing and GTM to Recruiting, Support, Internal Tools, and our Core Product.

In this role you will own a problem space and work closely with that function to design, build, and deploy production-grade agents, workflows, and applications that transform how we operate. Your work will directly accelerate LangChain’s mission to make intelligent, autonomous software a reality both internally and for our customers. Some of these projects will be open source, contributing to the LangChain and LangGraph ecosystem and setting new standards for how companies build with AI.

*This role will be based in our San Francisco or New York office. Employees within commuting distance work from the office are five days per week. Candidates who live outside commuting distance (e.g. >1hr each way), may be eligible for hybrid arrangements depending on location and role requirements.

## What You Will Do

- Design, implement, and deploy end-to-end AI workflows and agents that solve real problems across multiple business domains.
- Develop and iterate on agent architectures, evaluation pipelines, and performance frameworks to ensure reliability and measurable outcomes.
- Translate emerging AI research and tooling into practical, production-ready solutions.
- Communicate technical decisions, trade-offs, and insights clearly to both technical and non-technical stakeholders.
- Collaborate cross-functionally embedding with teams like Marketing, GTM, Recruiting, or Product to identify opportunities for agent-driven automation and measurable business impact.
- Contribute to the LangChain and LangGraph ecosystem, including open source components, documentation, and shared tools.

## What You Will Bring

- Experienced software engineer with a strong track record shipping AI or ML-powered applications (typically 3+ years, including at least 1 year building LLM systems in production).
- Hands-on experience implementing evaluation and monitoring systems for agents or workflows.
- Deep understanding of the components that make up an AI system: prompting, retrieval, orchestration, inference APIs, and model selection across modalities.
- Strong coding skills in Python or TypeScript (ideally both).
- Excellent communicator who can simplify complex technical ideas for diverse audiences.
- Thrives in a fast-moving, ambiguous startup environment; enjoys identifying the highest-impact problems and driving them to completion.
- Naturally curious and motivated to learn new tools, frameworks, and approaches in applied AI.

Nice To Haves

- Expertise with LangChain or LangGraph.
- Experience building or maintaining open source projects.
- Background in applied AI research or agentic workflow development.
- Based in San Francisco (preferred), NYC, or Boston.

## Compensation

We offer competitive compensation that includes base salary, meaningful equity, and benefits such as health and dental coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation will vary based on role, level, and location. For team members in the EU and UK, we provide locally competitive benefits aligned with regional norms and regulations. Annual Annual Salary Range: $165,000 - $190,000 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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