At a Glance
- Tasks: Teach teams to build AI agents and run hands-on workshops for real product fluency.
- Company: Join a leading tech company shaping the future of AI with innovative solutions.
- Benefits: Competitive salary, equity, flexible vacation, and comprehensive health coverage.
- Other info: Dynamic environment with opportunities for travel and professional growth.
- Why this job: Make a real impact in AI development while sharing your passion for technology.
- Qualifications: 3+ years in LLM/agent applications and 2+ years in a customer-facing technical role.
The predicted salary is between 80100 - 97900 £ per year.
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.
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).
The Enablement team works directly with companies building AI agents for production, getting new LangChain customers off to a fast, confident start. We own onboarding and instructor-led education for our customers, and run focused advisory sprints for accounts that need deeper support on architecture and evaluation.
You will set the technical foundation for every new customer — teaching their teams to build effectively on the platform and advising on agent development and evaluation as they go. You are someone who's built real agent systems, can defend the tradeoffs in them, and genuinely loves teaching, whether that's a live workshop for 50 engineers or a 1:1 debugging session with one stuck developer.
- Own onboarding and education for new enterprise customers to get them building effectively on the platform, fast.
- Design and run live, hands-on workshops that build real product fluency, not just familiarity.
- Create enablement assets (tutorials, reference implementations, best-practice guides) that scale beyond 1:1 time.
Requirements:
- 3+ years building LLM/agent applications — you've designed real agent architectures and evaluation strategies, not just wired up an API call.
- Strong Python, comfortable writing and debugging code live, in front of a customer.
- 2+ years in a technical, customer-facing role (Enablement, Customer Success Engineering, Solutions Engineering, or similar), including experience designing and delivering live workshops.
- Willing to travel up to 20% for customer engagements.
- You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks.
- Experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts.
- TypeScript/JavaScript in addition to Python.
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. Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
AI Solutions Developer employer: Langchain
At LangChain, we pride ourselves on being an innovative employer that empowers our team members to make a significant impact in the rapidly evolving field of generative AI. Our collaborative work culture fosters creativity and growth, providing ample opportunities for professional development while offering competitive compensation and comprehensive benefits tailored to the Australian market. Join us in shaping the future of intelligent agents and enjoy the unique advantage of working in a dynamic startup environment where your contributions truly matter.
StudySmarter Expert Advice🤫
We think this is how you could land AI Solutions Developer
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Langchain or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Langchain.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Langchain.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Langchain that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace AI Solutions Developer
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Langchain.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Langchain and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Langchain
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Langchain uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
