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For Companies At a Glance
- Tasks: Co-architect and build AI agents with customer teams, ensuring reliable production systems.
- Company: Join LangChain, a leading tech company revolutionising AI agent engineering.
- Benefits: Competitive salary, equity, flexible vacation, and comprehensive health coverage.
- Other info: Dynamic team environment with opportunities for growth and innovation.
- Why this job: Make a real impact on AI technology and work on challenging problems.
- Qualifications: 3+ years in a technical role, strong Python and JavaScript skills.
The predicted salary is between 60000 - 80000 £ per year.
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, LangChain, LangGraph, LangSmith, and Fleet 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.
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.
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
What You’ll Bring
- 3+ 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
- Native French Speaker
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 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.
Deployed Engineer (South EMEA) in London employer: Langchain
Contact Detail:
Langchain Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Deployed Engineer (South EMEA) in London
✨Tip Number 1
Get to know the company inside out! Research LangChain's products and their impact on AI agents. This will help you tailor your conversations and show genuine interest during interviews.
✨Tip Number 2
Network like a pro! Connect with current employees on LinkedIn or attend industry events. Building relationships can give us insights into the company culture and potentially lead to referrals.
✨Tip Number 3
Prepare for technical discussions! Brush up on your Python and JavaScript skills, and be ready to discuss your past projects. We want to see how you tackle real-world problems, so have examples ready!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re serious about joining the team at LangChain.
We think you need these skills to ace Deployed Engineer (South EMEA) in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Deployed Engineer role. Highlight your experience with AI agents and any relevant technical skills, like Python or JavaScript, to show us you’re a great fit!
Showcase Your Impact: When detailing your past experiences, focus on the impact you made in previous roles. We love to see how you've contributed to projects, especially in production environments, so don’t hold back!
Be Clear and Concise: Keep your application clear and to the point. Use straightforward language to explain your technical expertise and how it relates to the role. We appreciate clarity and want to understand your skills quickly!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Langchain
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python, JavaScript, and systems fundamentals. Brush up on your experience with agent-based applications and be ready to discuss specific projects where you've designed multi-step workflows or handled failures.
✨Showcase Your Customer Interaction Skills
Since the role involves working directly with customers, prepare examples of how you've successfully communicated technical concepts to non-technical audiences. Think about times when you’ve built trust and guided clients through evaluations or architecture reviews.
✨Prepare for Technical Demos
Be ready to run through a technical demo or training session during your interview. Practice explaining your thought process clearly and concisely, as this will demonstrate your ability to engage with developer audiences effectively.
✨Emphasise Your Problem-Solving Mindset
LangChain is all about tackling real-world problems, so come prepared with examples of how you've taken ownership of outcomes in previous roles. Highlight situations where you’ve had to figure things out on the go and how you approached those challenges.