We're on a mission to make it easy to build the LLM apps of tomorrow, today. We build products that enable developers to go from an idea to working code in an afternoon and in the hands of users in…
We're on a mission to make it easy to build the LLM apps of tomorrow, today. We build products that enable developers to go from an idea to working code in an afternoon and in the hands of users in…
What they do: Open-source framework and commercial platform for building, observing, evaluating, and deploying AI agents
Founding: Originated as Harrison Chase's open-source project (Oct 2022); company formed with co‑founder Ankush Gola in early 2023
Flagship products: LangChain framework, LangGraph, Deep Agents, LangSmith
Recent funding signal: Raised a growth round (~$100M–$125M) in 2025 valuing the company above $1B
Company Overview
Problem Domain
Agent engineering for large language model applications
Founded
2023
Industry
Technology, Information and Internet
Tech Stack
Open-source Python framework (LangChain)
Orchestration/runtime (LangGraph)
Agent tooling (Deep Agents)
Observability/deployment platform (LangSmith)
Funding Track Record
Seed- April 2023
$10M
Series A- February 2024
$25M
Reported valuation around $200M
Series B / Growth- 2025
$100M–$125M
Reported valuation above $1B (~$1.1B–$1.25B)
Investor Signal
“Participation from institutional and strategic investors including IVP, Sequoia, Benchmark, ServiceNow Ventures, Workday Ventures, Cisco Investments, Datadog Ventures, Databricks Ventures, and Frontline”
Founders
What we do
Join the Team
Partner Engineer
On-SiteSan Francisco, CA, US
On-Site • San Francisco, CA, US
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About LangChain
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.
Today,
LangChain, LangGraph, LangSmith, and Agent Builder
are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like
Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500
.
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.
About The Role
We're hiring our first Partner Engineer to define how the world's leading enterprises and technology partners adopt agentic AI using LangChain, LangGraph, and LangSmith. This is not a typical SA role. You'll be at the center of the agentic AI ecosystem, working with leading cloud providers, technology ISVs, and global system integrators to shape how production AI agents get built, deployed, and delivered at scale. You'll own the technical foundation of our partner ecosystem, from building reference architectures with cloud and ISV partners to standing up LangChain's first services partner enablement program, including certification tracks, hands-on workshops, and delivery playbooks that enable SIs and GSIs to implement agentic AI solutions for their customers independently. You'll have a direct line to our product and engineering teams, influence our technical roadmap, and help define the patterns that enterprises and their implementation partners use to go from prototype to production.
What You'll Do
How to Be Successful in the Role
Compensation And Benefits
We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. 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.
Annual salary range: $170,000 to $200,000 USD
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Partner with leading cloud providers, technology ISVs, services companies, and global system integrators (GSIs) to design and build agentic AI solutions that showcase what's possible with LangChain, LangGraph, and LangSmith
Create production-grade reference architectures, sample repositories, solution accelerators, and integration patterns that partners can take to their customers
Own technical relationships with partner engineering, architecture, and delivery teams, influencing their AI roadmaps, practice development strategies, and integration priorities
Design and build LangChain's services partner enablement program from the ground up, including tiered certification tracks (sales and technical), structured onboarding journeys, and partner readiness assessments
Lead hands-on technical workshops, bootcamps, and immersion sessions for SI/GSI partner teams, training their architects and developers to design, build, and deploy agentic AI solutions using LangChain's stack
Develop delivery playbooks, implementation guides, and hands-on labs that enable services partners to execute customer projects independently and at a high quality bar
Support strategic customer implementations alongside partner teams, serving as a technical escalation point for complex agent architectures, evaluation frameworks, and production deployment patterns
Build industry-specific agentic AI solutions (financial services, healthcare, retail, etc.) that services partners and GSIs can customize and deploy for their clients
Author technical content (blog posts, architecture guides, whitepapers) that establishes LangChain's point of view on agentic AI and serves as foundational enablement material for the partner ecosystem
Capture field learnings, partner feedback, and delivery patterns from SI engagements, translating them into actionable insights for product, engineering, and partnerships teams
Create repeatable playbooks and enablement materials that help our sales, partner, and services teams scale
Work at the intersection of engineering, product, partnerships, and GTM, translating partner and customer needs into scalable technical solutions
5+ years in technical, customer-facing or partner-facing roles such as Solutions Architect, Sales Engineer, Partner Engineer, Forward Deployed Engineer, or Applied AI Engineer
Strong Python skills and hands-on experience building and deploying solutions on at least one major cloud platform (AWS, Azure, or GCP)
Experience working with LLMs, RAG, agents, orchestration frameworks, or ML infrastructure
Experience enabling services companies, consulting firms, or global system integrators (GSIs), with an understanding of how they scope projects, staff delivery teams, and measure engagement success
Demonstrated ability to design and deliver technical training programs, workshops, or certification tracks for external partner audiences of varying technical proficiency
Ability to collaborate effectively with external partners on complex technical projects, including navigating multi-stakeholder environments across partner architects, delivery leads, and practice managers
Strong communication skills and comfort explaining technical concepts to both technical and non-technical audiences
Startup DNA: the ability to thrive in a fast-paced, scaling environment and build programs from scratch with limited existing infrastructure
Experience taking generative AI or agent-based systems from prototype to production, preferred
Hands-on experience with LangChain, LangGraph, LangSmith, or similar agent frameworks would be a big bonus
Experience building partner enablement content (labs, reference architectures, delivery playbooks) or standing up partner certification/readiness programs is a strong plus
Familiarity with SI/GSI delivery models, enterprise software deployments, or large-scale developer platform enablement is highly valued
