£Up to 180,000 GBP
Onsite WORKING
Location: Central London, Greater London - United Kingdom Type: Permanent

Director of AI Engineering
UK | Hybrid

Director Level | Technology Strategy

Overview

We are seeking a Director of AI Engineering, on behalf of a global Professional Services firm, to lead the strategy, design, and enterprise-wide adoption of Artificial Intelligence, Machine Learning, and Intelligent Automation capabilities.

This is a senior leadership role at the intersection of technology, strategy, and commercial impact, responsible for scaling AI across a complex global organisation. You will define the AI vision, build high-performing teams, and deliver transformative solutions that unlock measurable business value.

You’ll work closely with C-suite stakeholders, global engineering teams, and external partners to embed AI-first thinking, accelerate innovation, and shape the future of intelligent enterprise systems-including emerging paradigms such as the agentic web.

Key Responsibilities

Strategic Leadership & Governance

• Define and execute the enterprise-wide AI & Intelligent Automation strategy
• Establish frameworks for Responsible AI, ethics, and model governance (e.g. EU AI Act, NIST AI RMF)
• Act as executive sponsor for AI architecture, operating model, and adoption roadmap

AI & GenAI Ecosystem

• Lead the design and deployment of scalable AI solutions across Python, .NET, and cloud-native platforms
• Drive adoption of advanced frameworks (PyTorch, TensorFlow, Hugging Face, LangChain)
• Oversee integration of LLMs (OpenAI, Anthropic, Gemini, Mistral) via enterprise platforms (Azure OpenAI, Vertex AI)
• Implement RAG architectures and manage vector databases (Pinecone, Weaviate, FAISS, Milvus)

Data & Engineering Excellence

• Lead the evolution of modern data platforms (Databricks, Snowflake, Synapse, BigQuery)
• Ensure robust data engineering practices (Airflow, dbt, Prefect) and governance (Collibra, Purview)
• Drive scalable lakehouse architectures (Delta Lake, Iceberg, Hudi)

Cloud, Infrastructure & MLOps

• Champion multi-cloud engineering across Azure, AWS, and GCP
• Lead MLOps strategy (MLflow, Kubeflow, SageMaker, Vertex AI) and CI/CD pipelines
• Ensure scalable deployments using Kubernetes, Docker, and Infrastructure-as-Code

Enterprise Integration (.NET Focus)

• Integrate AI capabilities into enterprise-grade .NET ecosystems
• Modernise legacy systems using microservices, APIs, and event-driven architectures
• Embed DevSecOps best practices across all engineering workflows

Intelligent Automation

• Drive enterprise automation using tools like Power Automate, Blue Prism, and Automation Anywhere
• Implement cognitive services (NLP, speech, vision) to enhance digital workflows
• Lead process mining and optimisation initiatives (e.g. Celonis)

Analytics & Decision Intelligence

• Deliver data-driven insights through advanced analytics and BI platforms (Power BI, Looker)
• Enable predictive modelling and optimisation using modern ML toolkits

Security, Compliance & Responsible AI

• Ensure alignment with enterprise security standards (SOC2, ISO27001, NIST)
• Champion explainability, bias mitigation, and ethical AI practices

Leadership & Talent

• Build and lead high-performing global teams across AI, data, and automation
• Foster a culture of innovation, experimentation, and continuous learning
• Develop strategic partnerships across academia, startups, and hyperscalers

Your Background

• Proven experience leading enterprise-scale AI transformation programmes
• Deep technical expertise across Python, .NET, cloud platforms, and MLOps
• Strong understanding of data governance, architecture, and DevSecOps
• Demonstrated ability to deliver measurable business outcomes and ROI
• Exceptional stakeholder management and executive communication skills

Additional Information

Travel: Up to 60%

Why This Role?

This is a rare opportunity to define and lead AI strategy at scale, shaping how an organisation leverages cutting-edge technologies to transform operations, decision-making, and customer outcomes.

You won’t just implement AI-you’ll set the direction for its future.

Reference: AMC-TEL/DAI

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