Director of AI Engineering in Tech Catalyst UK

Role Overview

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 scale—accelerating 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 with .NET 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 practices—SonarQube , Checkmarx , Vault , and Azure API Management —aligned 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 ecosystem—academic institutions, hyperscalers, and startups—to identify strategic partnerships and emerging opportunities.

Preferred Background

• 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.

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