Lead Applied AI Engineer

Gravitas is proud to be partnering with a high-growth AI and technology consultancy as they continue to expand their industry-leading Applied AI and MLOps practice.

This is an opportunity to join a business at the forefront of AI innovation, helping organisations across multiple sectors transform ambitious AI concepts into secure, scalable, production-grade solutions. From venture-backed startups to enterprise organisations and public sector clients, you'll work on projects that deliver real-world impact while staying close to the latest advancements in AI, machine learning and cloud technologies.

We're looking for an experienced technical leader who enjoys combining hands-on engineering with customer engagement, project ownership and team leadership.

As a Lead Applied AI Engineer, you'll take ownership of the technical delivery of client projects while remaining deeply involved in the engineering process. You'll lead multidisciplinary teams through the entire delivery lifecycle, from discovery and prototyping to deployment and optimisation.

This role is ideal for someone who thrives in a consulting environment, enjoys solving complex customer challenges, and is passionate about taking AI systems from experimentation to production.

• Own technical delivery across client engagements
• Design and build production-grade AI and machine learning systems
• Work directly with customers to define solutions and shape strategy
• Mentor and develop engineers within delivery teams
• Contribute to pre-sales activities, proposals and solution design
• Influence technical direction and engineering best practice across the organisation

• LLM-powered applications
• Retrieval Augmented Generation (RAG) systems
• AI agents and autonomous workflows
• Model serving and inference platforms
• Evaluation and observability frameworks
• Cloud-native AI infrastructure
• MLOps platforms and deployment automation

You'll be expected to make pragmatic technical decisions that balance innovation, delivery speed, security, maintainability and commercial objectives.

• Lead the successful delivery of Applied AI and Machine Learning projects
• Remain hands-on with software development while providing technical leadership
• Guide architecture, engineering standards and technical decision-making
• Work closely with clients to understand business needs and define solutions
• Lead sprint planning, technical reviews and agile delivery processes
• Mentor engineers and support their professional development
• Manage technical risks and ensure high-quality project outcomes
• Contribute to hiring, interviewing and team growth
• Support business development through technical proposals and solution design
• Stay ahead of emerging trends across AI, ML, MLOps and cloud technologies

• Strong experience developing and deploying production-grade Python applications
• Experience building and delivering machine learning or generative AI solutions
• Commercial experience with technologies such as: LLMs, RAG architectures, Embeddings, Prompt engineering, Model evaluation, AI agents, ML workflows and model serving
• Experience designing cloud-native systems on AWS, Azure or Google Cloud
• Strong Dev Ops and Infrastructure-as-Code knowledge
• Proven experience leading technical delivery across teams, projects or work streams
• Experience mentoring or managing engineers
• Knowledge of:
  Git, Linux/Unix, Docker, Open-source AI, ML and MLOps tooling
• Excellent stakeholder and client-facing communication skills

Applications are welcomed from individuals with backgrounds in:

• Software Engineering
• Machine Learning Engineering
• Data Science

You don't need to already hold an "Applied AI" title. Strong engineering foundations, leadership experience and a passion for AI innovation are the most important factors.

• Salary of £80,000 - £100,000 depending on experience
• Equity options scheme
• 25 days holiday, increasing with service up to 30 days
• Enhanced maternity, paternity and adoption leave
• £500 annual learning and development budget
• AI assistant subscription of your choice
• Cycle to Work scheme
• Volunteer and charity days
• Regular company socials and events
• Structured career progression within a rapidly growing business

This is a hybrid role based in Manchester, with employees expected onsite three days per week (Monday, Wednesday and Thursday).

Occasional travel to customer sites throughout the UK may be required depending on project needs.

Due to the nature of some client engagements, successful candidates will need to be eligible for UK Security Clearance (SC level). As a result, applicants must typically have lived in the UK continuously for at least five years.