Head Of Applied Ai
About the Role
Lead and grow Colibri Digital's Applied AI practice, shaping technical direction, client engagements, and commercial propositions to move LLM-based and agentic AI from prototype to governed production. The role combines senior client-facing consulting, hands-on technical oversight, and responsibility for team development and practice growth.
Focuses on productionising LLM-based systems (RAG, agents, vector DBs) and building MLOps/LLMOps practices — hands-on AI engineering leadership rather than just prototyping.
Location: United Kingdom
Salary: Salary mentioned (no range provided)
Type: Full Time
Posted: Yesterday
Category: AI/ML & Data
Vibe Markers: 💻 Open Source, 🔥 Hot
Experience Level: Senior
Job Description
Role
Head of Applied AI responsible for leading and expanding Colibri Digital’s AI engineering capability, driving applied AI solutions from discovery through to reliable, governed production. Reports to the Chief Services Officer and works across sales, pre-sales, consulting and delivery.
Key Responsibilities
- Own the Applied AI capability: technical direction, standards, people, propositions and growth.
- Lead senior client conversations: AI discovery, consulting and solution definition from opportunity to delivery.
- Ensure AI engineering excellence across architecture, testing, CI/CD, MLOps/LLMOps, evaluation, security and governance.
- Drive production AI: move solutions beyond experimentation into reliable, scalable production environments.
- Challenge solution design, architecture, estimates and delivery approaches before commitments are made.
- Lead, mentor and develop AI engineers and senior technical specialists; build capability for the future.
- Support commercial growth: work with sales and pre-sales to build pipeline, win work and expand client relationships.
- Productise successful client solutions into repeatable propositions, accelerators and reusable IP.
- Help manage practice performance including revenue, utilisation, capacity and margin.
- Build market presence through clients, partners, events, content and thought leadership.
Requirements
- Deep technical expertise in modern AI engineering, especially LLM-based systems, RAG, agentic or multi-agent architectures, vector databases/embeddings and AI evaluation.
- Proven experience taking AI/ML solutions from prototype to production.
- Strong software engineering fundamentals: system design, APIs, version control, automated testing and CI/CD.
- Experience operating AI systems in production (MLOps/LLMOps) and with modern cloud AI technologies/platforms.
- Experience leading engineers while retaining technical credibility.
- Experience working directly with senior clients, ideally within consulting or professional services, including pre-sales activities (discovery, solution shaping, proposals, pitches).
- Track record of leading, mentoring and developing technical people and an understanding of responsible AI, governance and safe deployment at scale.
- Commercial awareness and ability to move between high-level business/value conversations and detailed technical discussions.
Who will thrive
- Entrepreneurial, curious leaders comfortable operating where answers are not always known.
- People able to experiment with emerging technologies and make pragmatic decisions about real value versus hype.
- Candidates from both small consultancies and larger consulting organisations who can take ownership and build practice-level playbooks.
Benefits
- Highly competitive salary (dependent on experience)
- Salary Sacrifice Pension plan (5+3)
- 25 days annual leave plus 1 birthday day
- Private medical and wider benefits
- Remote-first within the UK (travel to client sites, partner events and offices including central London as required)
Interview process
- Talent conversation
- Leadership conversation (AI leadership, consulting, commercial experience)
- Technical/working session (Applied AI approach, architecture, production)
- Practice/peer conversations
- Executive conversation
(Some stages may be combined depending on availability.)
Tech Stack
Generative AI, Agentic AI, Predictive AI, LLM-based systems, RAG, Agentic architectures, Multi-agent architectures, Vector databases, Embeddings, MLOps, LLMOps, CI/CD, APIs, Version control, Automated testing, Cloud AI platforms
Skills
AI Leadership, Applied AI, System Design, Architecture, MLOps/LLMOps, AI Governance, AI Evaluation, Software Engineering Fundamentals, CI/CD, Automated Testing, Version Control, Client Engagement, Pre-sales, Commercial Strategy, Team Leadership, Mentoring, Solution Design, Productisation
Benefits
- Highly competitive salary (dependent on experience)
- Salary Sacrifice Pension plan (5+3)
- 25 days annual leave + 1 birthday day
- Private Medical
- Wider benefits
- Remote-first within the UK
- Travel to client sites and offices