At a Glance
- Tasks: Design and deploy cutting-edge AI systems for Fortune 500 companies.
- Company: Distyl AI, a leader in applied AI technology with a mission-driven culture.
- Benefits: Competitive salary, equity, flexible time off, and private medical insurance.
- Other info: Collaborative environment with opportunities to work on high-impact projects.
- Why this job: Transform complex workflows and make a real impact with innovative AI solutions.
- Qualifications: 3+ years in software engineering, strong Python or TypeScript skills, and AI application experience.
The predicted salary is between 70000 - 90000 £ per year.
About Distyl AI
Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission‑critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys. Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. The results reflect this approach: a 100% production deployment success rate for our customers and one of the few enterprise AI companies to run a profitable business.
What We’re Looking For
We’re opening an office in London, UK and looking for AI Engineers to design and deploy production‑grade AI systems powered by LLMs. At Distyl, AI Engineers work directly with Fortune 500 companies to transform complex workflows using cutting‑edge AI. You’ll build and ship real‑world AI applications — from intelligent agents to full‑stack AI products — and see them operate at scale in mission‑critical environments. This role is highly hands‑on. You’ll collaborate closely with customers, define system architectures, and build reliable, high‑impact AI systems from prototype to production. Engineers at Distyl also help shape technical direction across major customer engagements, guiding enterprise teams through AI adoption and deployment.
Key Responsibilities
- Build Production AI Systems: Design, develop, and deploy robust AI applications using LLMs, including prompt engineering, agent workflows, tool use, and full‑stack AI products.
- Work Directly with Customers: Partner closely with enterprise stakeholders to understand complex problems and translate them into impactful AI solutions.
- Lead System Architecture: Design scalable architectures for production AI systems, balancing performance, reliability, cost, and maintainability.
- Develop Our Internal Platform: Contribute to Distillery, our internal LLM application platform, by building reusable infrastructure, tools, and workflows used across customer deployments.
- Evaluate AI Systems Rigorously: Develop evaluation frameworks that measure model performance across accuracy, latency, cost, reliability, and safety.
- Ship Production-Grade Systems: Ensure systems meet high standards for observability, reliability, security, and maintainability.
- Raise the Engineering Bar: Improve development workflows, evaluation practices, and deployment strategies as our AI platform continues to evolve.
Who You Are
- 3+ years of professional software engineering experience.
- Strong proficiency in Python or TypeScript.
- Experience building and deploying LLM‑powered applications or AI agents in production.
- Experience with modern LLM tooling such as LangChain, LlamaIndex, Guardrails, MCP, or agent frameworks.
- Experience implementing RAG pipelines, tool use, or multi‑step AI workflows.
- Strong understanding of AI system evaluation, debugging, and observability.
- Experience building reliable production systems with modern DevOps practices.
- Experience deploying AI systems in enterprise environments is a plus.
- Experience working across cloud platforms (AWS, GCP, or Azure) is a plus.
- Experience with agent architectures and long‑horizon task execution is a plus.
- Familiarity with responsible AI practices, including auditability and governance is a plus.
What We Offer
- Competitive salary, meaningful equity, and a comprehensive benefits package.
- Workplace Pension Scheme with employer contributions.
- Private Medical Insurance (PMI) offered.
- Flexible Time Off + Holidays.
- Lunch provided on office days.
- Access to state‑of‑the‑art models, generous usage of modern AI tools, and real‑world business problems.
- Ownership of high‑impact projects across top enterprises.
- A mission‑driven, fast‑moving culture that prizes curiosity, pragmatism, and excellence.
AI Engineer employer: jobr.pro
Distyl AI is an exceptional employer, offering AI Engineers the opportunity to work at the forefront of applied AI technology in a dynamic London office. With a strong focus on employee growth, competitive salaries, and a comprehensive benefits package, including private medical insurance and flexible time off, Distyl fosters a mission-driven culture that values curiosity and excellence. Employees will engage in high-impact projects with Fortune 500 companies, ensuring meaningful contributions to transformative AI solutions.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the AI field, especially those at companies you're interested in. Use platforms like LinkedIn to connect and engage with them — you never know who might help you land that interview!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving LLMs. This is your chance to demonstrate what you can do, so make it visually appealing and easy to navigate.
✨Tip Number 3
Prepare for technical interviews by practicing coding challenges and system design questions. Brush up on your Python or TypeScript skills, and be ready to discuss your experience with AI systems and architectures.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to engage directly with us.
We think you need these skills to ace AI Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI Engineer role. Highlight your experience with LLMs and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for AI and how you can contribute to our mission at Distyl. Be sure to mention specific technologies or methodologies you’ve used that relate to the job.
Showcase Your Projects:If you've built any AI applications or systems, don’t hold back! Include links to your GitHub or portfolio. We love seeing real-world examples of your work and how you tackle complex problems.
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 shows you’re keen on joining our team!
How to prepare for a job interview at jobr.pro
✨Know Your AI Stuff
Make sure you brush up on your knowledge of LLMs and the specific technologies mentioned in the job description, like LangChain and Guardrails. Be ready to discuss your past experiences with these tools and how you've used them to solve real-world problems.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of complex problems you've tackled in previous roles. Think about how you translated those challenges into impactful AI solutions, especially in production environments. This will demonstrate your ability to work directly with customers and understand their needs.
✨Architectural Insights Matter
Since you'll be leading system architecture, be prepared to discuss your approach to designing scalable AI systems. Talk about how you balance performance, reliability, and cost, and maybe even share a few architectural diagrams if you can!
✨Emphasise Collaboration
Highlight your experience working closely with enterprise stakeholders. Discuss how you’ve guided teams through AI adoption and deployment, and be ready to explain how you ensure that everyone is on the same page during projects.
