Director of AI Engineering in Tech Catalyst UK

The Director for AI & Intelligent Automation will define and execute the enterprise strategy for Artificial Intelligence Machine Learning and Automation across business domains.

This role blends technical excellence strategic leadership and commercial acumen combining deep expertise in Python .NET and cloud-native architectures to deliver scalable secure and value-generating intelligent systems leveraging the latest in thinking in the future agentic web.

The MD/D will partner with C-suite executives technology leaders and global delivery teams to embed AI capabilities at scaleaccelerating innovation enhancing decision-making and transforming enterprise operations.

Key Leadership Responsibilities

Strategic Vision & Governance

• Define the global AI & Intelligent Automation strategy ensuring alignment with enterprise digital transformation and innovation objectives.

• Establish governance frameworks for AI ethics model transparency and Responsible AI ensuring compliance with regulatory and risk standards (e.g. NIST AI RMF EU AI Act).

• Serve as the senior executive sponsor for AI architecture operating model and adoption roadmap.

Enterprise AI & GenAI Ecosystem but not exhaustive or limited by

• Oversee the design and deployment of enterprise-grade AI solutions using Python .NET and cloud-based MLOps pipelines.

• Direct teams leveraging advanced frameworks including PyTorch TensorFlow Hugging Face ONNX Runtime and LangChain integrating orchestration tools like Semantic Kernel LangGraph and CrewAI

• Drive responsible integration of Large Language Models (LLMs) from OpenAI Anthropic Google Gemini and Mistral including deployment via Azure OpenAI Service or Vertex AI.

• Implement retrieval-augmented generation (RAG) architectures and manage vector databases such as Pinecone Weaviate FAISS and Milvus to support enterprise knowledge intelligence systems.

Data Platform & Engineering Excellence

• Lead the evolution of the enterprise data estate leveraging modern data platforms such as Databricks Snowflake Azure Synapse and BigQuery.

• Oversee data engineering using Apache Airflow dbt and Prefect ensuring data pipelines are performant governed and aligned with enterprise metadata standards (Collibra Alation Microsoft Purview).

• Drive the adoption of Delta Lake Iceberg and Hudi for scalable data lakehouse architectures.

• Ensure high-quality compliant data foundations for machine learning and analytics workloads.

Cloud Infrastructure & MLOps

• Champion multi-cloud architecture and engineering excellence across Azure AWS and GCP.

• Ensure resilient and cost-effective deployment via Docker Kubernetes (AKS/EKS/GKE) and Terraform/Bicep.

• Lead enterprise MLOps initiatives using Azure ML SageMaker Vertex AI MLflow and Kubeflow with continuous integration pipelines (GitHub Actions Azure DevOps Jenkins Argo CD).

• Oversee monitoring and observability using Prometheus Grafana ELK/EFK and OpenTelemetry.

Enterprise Integration Ecosystems

• Guide integration of AI/ML workflows into enterprise-grade .NET Core applications and service-oriented architectures.

• Modernize legacy systems through microservices REST/gRPC APIs and message-driven solutions (Azure Service Bus Kafka).

• Implement secure and compliant DevSecOps practicesSonarQube Checkmarx Vault and Azure API Managementaligned to enterprise standards.

Intelligent Automation & Cognitive Services

• Drive end-to-end intelligent automation using Power Automate Blue Prism and Automation Anywhere.

• Integrate cognitive services including Azure Cognitive Services AWS Comprehend Form Recognizer and Speech/Translation APIs to augment digital workflows.

• Lead enterprise process mining and optimization initiatives via Celonis Power BI Process Mining and ProcessGold.

Analytics BI and Decision Intelligence

• Oversee the integration of analytics and AI to deliver measurable business outcomes.

• Advance enterprise analytics using Power BI Looker and Azure Analysis Services.

• Foster data-driven decisioning through predictive and optimization models using PyCaret Prophet and Optuna.

Security Compliance & Responsible AI

• Ensure alignment with enterprise security standards and frameworks (SOC2 ISO27001 NIST).

• Oversee identity and access management through Azure AD OAuth2 OpenID Connect and integration with enterprise IAM systems.

• Champion ethical AI bias detection and explainability through Azure Responsible AI Dashboard and equivalent frameworks.

Leadership Talent & Innovation

• Build and lead high-performing global teams in data science engineering and automation disciplines.

• Cultivate a culture of innovation continuous learning and responsible experimentation.

• Engage with the external AI ecosystemacademic institutions hyperscalers and startupsto identify strategic partnerships and emerging opportunities.

Preferred Background

• 15 years in technology or consulting leadership with significant experience delivering enterprise AI data and automation transformations.

• Proven record integrating Python-based AI with .NET enterprise systems.

• Deep expertise across multi-cloud environments data governance and enterprise DevSecOps.

• Demonstrated ability to deliver large-scale transformation programs and measurable ROI.

• Strong executive presence communication and client/stakeholder management skills.