AI Engineer (London)
AI Engineer (London)

AI Engineer (London)

Full-Time 70000 - 90000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Build AI agents that learn and automate enterprise processes using cutting-edge technology.
  • Company: Join Edra, a Series A startup backed by top VCs, in a collaborative environment.
  • Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
  • Other info: Diverse team with a focus on exceptional talent and career development.
  • Why this job: Make a real impact in AI by solving complex problems with innovative solutions.
  • Qualifications: 3+ years of experience in building LLM-based systems and strong communication skills.

The predicted salary is between 70000 - 90000 £ per year.

About Edra

Edra is solving one of the hardest problems in enterprise AI: AI models are generic but company processes are specific. We build AI agents that learn how processes actually run, and then run their operations. We’re a Series A startup, backed by Sequoia and other leading VC firms, and we’re growing our team in New York and London. We’re a deeply technical team of engineers, AI researchers, and strategists with a high bar for talent and a shared belief that exceptional people are the foundation of everything great we’ll build.

The Role

We’re building a learning system that teaches AI agents how enterprises actually work. Our system ingests knowledge bases, conversations, tickets, and system logs, then produces written instructions that agents can execute–with confidence scoring to know when to automate and when to seek human input. We’re looking for AI Engineers who have built complex, production LLM-based systems. Whether you’ve scaled LLM workflows handling millions of requests, built multi-agent systems in production, or designed evaluation frameworks for enterprise deployments, we want people who bring intensity and self-direction to their craft. You’ll work directly on our core learning library, ship features with real enterprise customers, and contribute back to the platform. The work spans continuous learning systems, agentic features, human-in-the-loop feedback loops, and agent orchestration.

What You’ll Do

  • Build and contribute to our core context learning library, implementing new learning capabilities with customers then generalizing them back into the platform
  • Design and implement LLM-powered systems and agentic workflows from concept to production
  • Work directly with enterprise customers to identify new problems, prototype solutions, and ship them to production
  • Build agentic features for knowledge management–think agents that can edit, update, and maintain large knowledge bases autonomously
  • Build reliability and confidence systems–evaluation frameworks, confidence scoring, and logic for when to automate vs. when to elevate to a human
  • Architect async, scalable systems that handle complex AI orchestration
  • Contribute to the direction of our AI strategy and product capabilities

What We’re Looking For

  • You’ve built complex, production LLM-based systems with real depth–something with multiple layers of engineering decisions you can walk through in detail
  • You’ve shipped something meaningful to production and can explain how it evolved
  • You’re excited by open-ended problems where the solution might not exist yet
  • You have experience with (or strong interest in) how systems learn and improve over time: human-in-the-loop feedback, prompt optimization and context engineering
  • You have experience building agents and autonomous systems
  • You can navigate between research papers and production code with equal comfort
  • You have 3+ years of professional experience
  • You’re a strong communicator who can clearly explain their work, both to teammates and to customers

Don’t meet all of the above traits? We’d still love to hear from you. We’re looking for exceptional people with unique skills and interests, and we know that great people have different backgrounds and skillsets.

A Few Details

Edra is an equal opportunity employer and we encourage applications from individuals of all backgrounds. Edra does not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, marital status, sexual orientation, gender identity, veteran status, or any other legally protected characteristic.

AI Engineer (London) employer: Edra

At Edra, we pride ourselves on being an exceptional employer, fostering a collaborative and innovative work culture that empowers our AI Engineers to tackle complex challenges in enterprise AI. Located in the vibrant city of London, we offer competitive benefits, opportunities for professional growth, and the chance to work alongside a deeply technical team dedicated to pushing the boundaries of AI technology. Join us to contribute to meaningful projects that shape the future of enterprise operations while enjoying a supportive environment that values diversity and creativity.
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Contact Detail:

Edra Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land AI Engineer (London)

✨Tip Number 1

Network like a pro! Reach out to people in the AI field, especially those at Edra or similar companies. A friendly chat can open doors and give you insights that a job description just can't.

✨Tip Number 2

Show off your skills! If you've built any LLM-based systems or agentic workflows, create a portfolio or a GitHub repo showcasing your work. This is your chance to shine and demonstrate your expertise.

✨Tip Number 3

Prepare for the interview by diving deep into Edra's projects and values. Understand their approach to AI and think about how your experience aligns with their mission. This will help you stand out as a candidate who truly gets it.

✨Tip Number 4

Don't hesitate to apply through our website! We love seeing passionate candidates who are eager to join our team. Even if you don't tick every box, your unique skills might be just what we're looking for.

We think you need these skills to ace AI Engineer (London)

LLM-based Systems Development
Agentic Workflows Design
Knowledge Management
Human-in-the-Loop Feedback
Prompt Optimization
Context Engineering
AI Orchestration
Scalable System Architecture
Production Code Navigation
Strong Communication Skills
Problem Identification and Prototyping
Continuous Learning Systems

Some tips for your application 🫡

Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the AI Engineer role. Highlight any projects or systems you've built that relate to LLMs or autonomous systems, as this will show us you're a great fit!

Craft a Compelling Cover Letter: Use your cover letter to tell us why you're excited about working at Edra. Share your passion for solving complex problems and how your background makes you the perfect candidate for our team.

Showcase Your Projects: If you've worked on relevant projects, don't hesitate to include links or descriptions in your application. We love seeing real examples of your work, especially if they demonstrate your ability to build and scale LLM-based systems.

Apply Through Our Website: For the best chance of getting noticed, make sure to apply through our website. This way, we can easily track your application and ensure it reaches the right people on our team!

How to prepare for a job interview at Edra

✨Know Your Stuff

Make sure you’re well-versed in the specifics of LLM-based systems. Be ready to discuss your past projects in detail, especially those that involved complex engineering decisions. This shows you’ve got the depth and experience they’re looking for.

✨Show Your Problem-Solving Skills

Edra is all about tackling open-ended problems. Prepare examples of challenges you've faced in previous roles and how you approached finding solutions. Highlight your creativity and ability to think outside the box.

✨Communicate Clearly

As a strong communicator, you’ll need to explain your work effectively to both teammates and customers. Practice articulating your thoughts on technical concepts in a way that’s easy to understand. This will demonstrate your ability to bridge the gap between research and production.

✨Be Ready for Technical Questions

Expect to dive deep into technical discussions during the interview. Brush up on topics like human-in-the-loop feedback, prompt optimisation, and context engineering. Being prepared to discuss these areas will show your genuine interest and expertise in the field.

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