Senior Applied AI Engineer: Software

About us

Fuzzy Labs is a fast-growing Applied AI engineering consultancy based in Manchester. We help organisations turn ambitious AI ideas into secure, reliable systems that work in the real world.

Our work runs from research and rapid prototypes through to production software, AI evaluation and cloud infrastructure at scale, for clients ranging from innovative startups and global organisations to policing and secure government. That means genuinely hard problems and real impact.

The role

We're looking for strong software engineers who want to apply their engineering experience to the rapidly evolving world of Applied AI.

You don't need to have spent your career in machine learning or have “AI Engineer” in your current job title.

You might be a backend, platform, full-stack or distributed-systems engineer who has spent several years building reliable production software and is now increasingly experimenting with LLMs, agents and AI-assisted development.

What matters is that you're an excellent engineer, you're excited about AI, and you learn quickly.

You'll join client-facing engineering teams building real Applied AI systems. Initially, your greatest contribution may be bringing strong software engineering practices to AI-shaped problems from architecture, APIs, services, data flows, testing, cloud infrastructure, observability and reliability, while developing deeper Applied AI expertise alongside experienced engineers.

Over time, we expect the boundary between AI Software Engineer and Applied AI Engineer to become increasingly blurred.

What you’ll do

• Design and build reliable production software around AI capabilities.
• Turn prototypes and experiments into maintainable production systems.
• Build APIs, services, integrations, data pipelines and user-facing capabilities where required.
• Work with LLMs, model APIs, RAG, embeddings, structured outputs, agents and tool use.
• Develop evaluation and testing approaches for systems whose behaviour isn't always deterministic.
• Deploy and operate systems using modern cloud, container and infrastructure practices.
• Work directly with customers to understand problems and turn ambiguous requirements into working software.
• Bring strong software engineering practices into multidisciplinary Applied AI teams.
• Use modern AI-assisted engineering tools effectively while maintaining high standards of engineering judgement.
• Learn rapidly from Applied AI Engineers, client projects and Fuzzy Labs R&D.
• Contribute your existing engineering expertise back into the wider team.

Why join Fuzzy Labs?

• Work at the frontier of Applied AI: shape how fast-moving AI technologies are used in production, using open source where it fits.
• Real impact: solve meaningful problems for innovative companies, AI safety and security teams, policing and secure government.
• Space to explore: dedicated time for R&D, open-source work, blogs and videos, and the chance to build your own voice in the applied AI community.
• Grow with us: take on more technical, client and leadership responsibility as the company grows.

The important details

• Equity: equity options, a genuine stake in Fuzzy Labs
• Office: modern central Manchester office with an on-site gym. We’re in on Mondays, Wednesdays and Thursdays.
• Travel: occasional visits to client sites across the UK
• Security clearance: you’ll need SC clearance after you start, which includes credit and criminal record checks, so we can only consider candidates with 5+ years’ UK residence
• Holiday: 25 days, rising to 30 with length of service
• Development: £500 annual budget, plus the AI assistant(s) of your choice
• Benefits: healthcare cash plan, enhanced maternity, paternity and adoption leave, Cycle to Work, volunteering time and company socials

Skills and experience

• Strong experience building and operating production software.
• Strong programming skills, with excellent Python knowledge as a core requirement. Experience with additional languages such as TypeScript, Java, Go or C# is highly valued.
• Strong understanding of software design, APIs, testing, debugging and maintainable code.
• Experience with cloud platforms and modern software delivery practices.
• Experience with modern CI/CD build pipelines, tooling and practices.
• Experience taking software from development through to production.
• An insatiable appetite for solving complex problems and learning new skills.

Applied AI

• We don't expect you to already be an AI specialist. Evidence of active development in this direction might include:
• Any applications of large language models (LLMs) including RAG or semantic search, agentic systems and structure tool use, and integrations into wider systems.
• Any experience of using model evaluation and monitoring for non-deterministic systems at scale or as hobby projects.
• Personal experimentation or side projects within the AI/LLM/ML domain.
• Any Open Source AI projects, side projects and experimentation.
• Keeping up to date with latest and greatest in AI frontier development, not specifically the finer details but being able to understand the direction of travel and where the space is moving towards.

Commercial AI experience is useful, but isn't required. Curiosity, evidence of learning and strong engineering foundations matter more.

Don’t tick every box? Apply anyway. Applied AI sits across software engineering, ML engineering, data science, DevOps and product delivery, so you don’t need “applied AI” in your job title. We care more about strong engineering foundations, leadership experience, what you know deeply and how quickly you learn.

Diversity, Equity & Inclusion

At Fuzzy Labs, we believe diverse teams build better technology. We're committed to creating an inclusive environment where everyone feels valued, respected and able to do their best work. We welcome applications from people of all backgrounds, experiences and perspectives, and encourage you to apply even if you don't meet every requirement listed in the job description.

Interested?

If you’d like to work with us, please use the link below. Include a few words about yourself and what interests you about the role, plus a link to your GitHub, Bitbucket or similar. If you’re on Kaggle, have a tech blog, a cool side project, or an Instagram for your cat, dog, etc, send us that too!

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