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Women in Data®

Director of AI Engineering in Tech Catalyst UK

London
Posted 1 day ago
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Locations: Belfast, Birmingham, Bristol, Edinburgh, Glasgow, London, Leeds, Manchester

About the Role

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.

What You'll Do

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.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

Start with a chat, not a search bar

Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.

Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

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

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  • 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.

This Role Is For You If You Have

  • 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.

What You'll Receive From Us

No matter where you may be in your career or personal life, our benefits are designed to add value and support, recognising and rewarding you fairly for your contributions. We offer a range of benefits including empowered flexibility and a working week split between office, home and client site; private medical cover and 24/7 access to a qualified virtual GP; six volunteering days a year and much more.

We offer a range of benefits including empowered flexibility and a working week split between office, home and client site; private medical cover and 24/7 access to a qualified virtual GP; six volunteering days a year and much more.

Women in Data® advertise roles on behalf of our partners, alliances, and members.

We are proud supporters of Women in Data. Connect, engage and belong to the largest free female data community in the UK – visit: www.womenindata.co.uk to join our community.

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Skills

Artificial Intelligence
Machine Learning
Python
.NET
Cloud-Native Architecture
MLOps
Generative AI
RAG
Data Governance
Strategic Leadership
DevSecOps
Intelligent Automation
Enterprise Architecture
Stakeholder Management
Data Engineering
Responsible AI

Location

London, England, United Kingdom

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