Lead Applied AI Engineer

About us

Fuzzy Labs is a fast-growing, Manchester-based tech consultancy that helps a diverse range of clients build, deploy, and productionise AI systems using open source technologies. We exist to help our customers harness and channel the power of AI safely and effectively, to make positive change and use AI for good.

Our work sits across the whole development lifecycle, from exploring and prototyping new AI use cases to building scalable, secure, production-grade machine learning and generative AI systems, and everything in between. Our work spans disruptive startups, multi-national organisations, policing, and secure government sectors, providing you with the unique opportunity to make a tangible, real-world impact.

We’ve had considerable growth over the last few years and we’re looking to continue with this momentum as we build on our reputation as Open Source MLOps and applied AI experts, expand our role within the community, and continue to deliver high-quality solutions to our clients.

What we’re looking for

The ideal candidate will be motivated to grow and progress in line with the company’s ambitions: we’re looking for passionate engineers with an appetite for keeping up with the cutting edge, an eye for detail, and a knack for creative problem solving.

This role suits experienced technical leaders looking for a forward-deployed engineering role where they can combine strong software engineering, applied AI, technical leadership, customer problem solving, and project ownership. You’ll work close to the people using what we build, helping turn ambiguous AI opportunities into reliable production systems that deliver real-world impact.

As a Lead Applied AI Engineer, we’ll look to you to lead engineering squads, own the technical delivery of client projects, shape technical direction, support and mentor engineers, and work confidently with customers from discovery through to production delivery.

As well as being a great engineer, motivated by the chance to be at the forefront of applied AI, you’ll also enjoy being part of a culture that values:

• Loving what we do: a real passion for open source, applied AI, MLOps, and taking pride in our work.
• Just trying it: AI is moving quickly. We love to develop new skills, solve new problems and thrive on a challenge.
• Being greater than the sum of parts: we are a team, one that isn’t just us but our customers and our community.
• Positive impact: AI is going to change the world. We choose to use it for good and leave a positive legacy.

A typical day

You’ll work within an engineering squad and take part in every stage of the project delivery lifecycle, including:

• Being hands-on with the technical delivery of projects. As a technical leader, you’ll be writing code while also setting the standard for engineering quality, delivery discipline and technical decision-making across the team.
• Working directly with clients to understand their needs, shape ambiguous problems, recommend appropriate solutions, and bring them along on the journey.
• Owning the delivery of client projects, from discovery and prototyping through to production deployment, handover and ongoing improvement.
• Leading the design and implementation of production-grade AI systems, including LLM-powered applications, retrieval augmented generation, model serving, evaluation frameworks, AI agents, data pipelines, cloud-native infrastructure, and MLOps workflows.
• Making pragmatic technical decisions that balance delivery speed, reliability, security, maintainability, user needs and commercial constraints.
• Leading sprint planning sessions, retrospectives and code reviews, ensuring the team is focused, unblocked and delivering high-quality work.
• Working as part of the team, sharing and reviewing ideas, mentoring and guiding team members through technology, architecture, implementation details and delivery trade-offs.
• Supporting your team members’ personal development objectives within client projects, helping them grow their technical judgement, client-facing confidence and ownership.
• Helping to grow the team by taking part in hiring and interviewing.
• Helping to write proposals for new clients, participating in the technical side of the sales process, and shaping credible delivery approaches for applied AI opportunities.
• Staying up-to-date with a fast-moving industry, embracing new tools and frameworks, and sharing your learnings with the team.

As well as client work, we also set aside time to work on R&D projects and produce content in the form of blogs and videos. These projects are how we keep on top of a fast-moving technology landscape, in addition to being our greatest source of marketing. You’ll have the opportunity to craft your own voice in the applied AI and MLOps community through R&D content.

Skills and Experience

Our team is made up of a mix of backgrounds. We are looking for smart, curious people who are always expanding their knowledge and exploring new and emerging technologies. If you get excited about keeping up with the newest AI tools, figuring out how to scale generative AI systems in the cloud, or turning prototypes into production software, then you’ll fit right in. Some of the skills and experience we look for include:

• An undergraduate degree in computer science, mathematics, or similar, or a relevant postgraduate degree.
• A passion for coding, machine learning, AI, open source technologies, and setting high standards for their implementation and adoption.
• Strong experience writing and deploying production-grade Python software. This could include training and serving machine learning models, building large-scale inference services, integrating data stores, building APIs, or deploying AI-powered applications.
• Experience with machine learning or generative AI systems, such as LLM-powered applications, RAG pipelines, embeddings, prompt engineering, model evaluation, agents, model serving, or ML workflows.
• Experience designing and delivering cloud-based systems, for example using AWS, Google Cloud or Azure, along with modern DevOps practices and infrastructure-as-code tooling.
• Experience leading technical delivery across a project, team or workstream, including planning implementation, managing technical risk, reviewing architecture, and supporting engineers through delivery.
• Experience managing, mentoring or supporting the development of software engineers.
• Experience delivering software using an agile development methodology.
• Fluency in our core software tooling: Git, Unix/Linux, Docker, and common open‑source AI, ML or MLOps tools. Plus, a strong opinion on your IDE / editor of choice is welcome ;)
• You should be aware of the broad landscape of AI and machine learning applications, tools, and technologies and willing to deepen your knowledge.
• Excellent communication skills, both in customer-facing and internal team communication.

We encourage you to apply even if you don’t meet all of the requirements. Applied AI is an emerging field, sitting at the intersection of software engineering, machine learning engineering, data science, DevOps and product delivery. We’re excited to speak to candidates from any of these backgrounds; you don’t need an explicit MLOps or applied AI job title already, as long as you have strong engineering foundations, leadership experience, and are excited to immerse yourself in this fast-moving field.

Benefits

By joining a growing company you’ll have the chance to make a real impact on its future. There’s plenty of room for growth and we’ll work with you to help you realise your technical and personal ambitions because your success and the company’s success are one and the same.

• 25 days holiday rising to 30 with each year of service
• Enhanced family leave, including maternity, paternity and adoption leave
• Healthcare cash plan
• £500 annual personal development budget and AI assistant of your choice
• Equity option scheme, giving you a genuine stake in the business
• Hybrid working in a vibrant, central Manchester office with free fruit, cereals, and hot & cold drinks
• Cycle to Work Scheme and secure bike storage
• Paid time off for charity and volunteering
• Company socials, summer and Christmas parties

Location and Eligibility

As a hybrid‑working organisation, we bring the team together in the office three days each week on Mondays, Wednesdays and Thursdays, and work remotely on the remaining days. We have found that regular, structured time in person enables us to make decisions more quickly, collaborate more effectively, and build the strong working relationships that underpin our work.

For that reason, being able to join us in our central Manchester office on those set days is an essential part of the role. At the same time, we recognise that personal circumstances vary. We aim to approach individual situations with flexibility and openness, and we’re always willing to have a conversation where specific needs arise.

Some client work may also involve occasional travel to customer sites across the UK. We see this as an important part of Applied AI: getting close to the people, systems and environments we’re building for. Travel will vary by project and will be planned with reasonable notice.

Finally, due to the sensitive nature of some projects, you will be required to undergo UK government security clearance after you start, at SC level. This will include a credit check and criminal records check. As a result, we’re only able to consider candidates who have been resident in the UK for 5 or more years.

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