Job Summary
UK based Remote First – Occasional Travel to London
Up to £130,000
This is an opportunity to take a leading role in building and shaping a growing AI capability within a consultancy environment, where you will combine hands‑on engineering leadership with client‑facing consulting and solution design. You will be responsible for delivering production‑grade AI solutions for enterprise clients, while helping define engineering standards, mentoring AI engineers, and influencing how AI capability is built, scaled, and delivered across multiple engagements. This role is ideal for someone who enjoys operating at the intersection of technical delivery, architecture, and stakeholder engagement, with a strong focus on turning AI concepts into real‑world business value.
Responsibilities
- Lead the design, build, and deployment of AI and machine learning solutions across enterprise client environments, including LLM and agentic solutions.
- Work closely with clients to understand business challenges, lead technical workshops, and translate complex AI concepts into clear, practical solution options.
- Guide delivery teams through implementation, ensuring engineering quality across CI/CD, testing, model monitoring, observability, and performance optimization.
- Shape solution architecture, evaluate AI tools and frameworks, and introduce best practices across MLOps, model lifecycle management, and responsible AI.
- Support pre‑sales activities and contribute to shaping AI roadmaps and client propositions.
- Provide technical leadership across multiple AI delivery teams, ensuring solutions are delivered to a high standard and aligned with client objectives.
- Build and deploy production‑grade ML and AI solutions, including model evaluation, monitoring, drift detection, and operational observability.
- Implement and oversee MLOps practices such as CI/CD pipelines, model registries, and Infrastructure as Code.
- Coach and mentor engineers, contribute to internal capability development, and help define reusable engineering patterns and accelerators across the AI practice.
Qualifications
- Experienced AI Engineers or AI Engineering Leads with a strong background in delivering production‑grade AI solutions in enterprise environments.
- Strong Python engineering skills and experience building and deploying ML or AI systems into production.
- Hands‑on experience with modern cloud AI platforms such as Azure AI services, Azure Machine Learning, Databricks, AWS SageMaker, or Bedrock.
- Strong understanding of MLOps practices, including CI/CD, model monitoring, observability, and infrastructure automation.
- Experience leading technical teams, guiding engineers, and delivering client‑facing AI solutions.
- Ability to translate complex AI concepts into clear, actionable guidance for both technical and non‑technical stakeholders.
- Experience with LLM‑based systems, agent frameworks, prompt engineering, vector databases, and orchestration tools (highly beneficial).
- Exposure to responsible AI practices, human‑in‑the‑loop (HITL) design, and enterprise AI governance frameworks (advantageous).
- Experience in consulting environments, pre‑sales support, or shaping AI strategy and roadmaps (strong plus). Familiarity across multiple cloud ecosystems.
Impact and Value
This role offers the opportunity to shape and deliver cutting‑edge AI solutions across enterprise organisations. Your work will directly influence how clients adopt and operationalise AI, bridging the gap between strategy and delivery and helping clients move from early AI exploration into production‑grade systems that deliver measurable business value.
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