LangChain
Data AI · LLM orchestration
- Website
- langchain.com
LangChain currently has 47 active AI-related job listings. The majority of these roles, 87%, are focused on agents, with the remaining 13% in evaluation. Engineering is the primary function being hired for, with 46 positions, while Product has one listing. The United States is the dominant hiring country, with 37 roles. Frequent tech tags include agent orchestration, LLM observability, and model serving, suggesting a focus on building and managing AI agent systems. In the last 30 days, LangChain posted 5 new AI roles, representing a 78% decrease compared to the previous 30-day period.
Currently tracking 45 active AI roles, down 54% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $116k–$340k (avg $196k).
Data AI · LLM orchestration
LangChain currently has 42 active AI-related roles in our index. The most common open titles are: GTM Engineer (2), Customer Engineer (West Coast), Deployed Engineer (Amsterdam), Deployed Engineer (Atlanta), Deployed Engineer (Bay Area). Most positions are in Engineering and Product.
LangChain's active AI hiring is concentrated in: agents (83%), evaluation (14%), serving infrastructure (2%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
LangChain is hiring AI talent in: United States (31 roles), United Kingdom (3 roles), Sweden (2 roles), Singapore (2 roles).
Job postings at LangChain most frequently reference: agent orchestration, llm observability, model serving, evals, guardrails.
In the past 30 days, LangChain has posted 3 new AI-related roles. That is a -89% change versus the prior 30 days (27 → 3).
| Title | Stage | AI score |
|---|---|---|
| Solutions Architect (London) LangChain is seeking a Solutions Architect to join their Professional Services team in London. The role involves designing, deploying, and optimizing AI infrastructure and agent systems for enterprise customers. Responsibilities include infrastructure engineering (Kubernetes, Terraform, CI/CD), agent engineering (multi-agent systems, evaluation, prompt optimization), and customer engagement. Requires 7+ years of technical customer-facing experience, with specific skills in cloud platforms, Kubernetes, LLM frameworks, and AI application development. | AgentServe | 9 |
| Deployed Engineer (South EMEA) LangChain is seeking a Deployed Engineer to work directly with companies building and running AI agents in production. This role involves co-architecting and co-building production AI agents, owning the technical win in pre-sales, helping customers deploy and operate agent-based applications, and advising on architecture and best practices. The ideal candidate has 3+ years of technical experience, strong Python/JavaScript skills, and experience designing agent-based or LLM-powered applications beyond simple API calls. |
| Agent |
| 8 |
| Deployed Engineer (UK) LangChain is seeking a Deployed Engineer in the UK to work with companies building and running AI agents in production. This role involves co-architecting and co-building agents, owning technical wins in pre-sales, helping customers deploy and operate agent-based applications, and advising on best practices. The ideal candidate has 3+ years of experience in a relevant technical role, strong Python/JavaScript skills, experience designing agent-based applications beyond simple API calls, and is comfortable working directly with customers. The role emphasizes operating AI agents in production and contributing to the platform's adoption. | Agent | 8 |
| Customer Engineer (London) LangChain is seeking a Customer Engineer for their Enterprise Enablement team in London. This role involves leading onboarding, delivering training, developing enablement frameworks, and acting as a liaison between customers and product/engineering teams. The ideal candidate has 5+ years in a technical customer-facing role, with 2+ years focused on AI/ML applications or agents, strong Python proficiency, and experience with the modern AI/LLM stack. The role emphasizes customer success and shaping best practices in agent engineering. | Agent | 7 |