AI Director

Role Specification

Strategic Vision & Governance

• Define the global AI & Intelligent Automation strategy, fully aligned with enterprise digital transformation and innovation goals.
• Establish governance frameworks for AI ethics, model transparency, and Responsible AI, ensuring adherence to regulatory and risk requirements (e.g., NIST AI RMF, EU AI Act).
• Serve as the senior executive sponsor for AI architecture, operating model design, and enterprise adoption roadmap.

Enterprise AI & GenAI Ecosystem (not exhaustive or limiting)

• Oversee the design and deployment of enterprise‐grade AI solutions using Python, .NET, and cloud‐native MLOps pipelines.
• Direct teams working with advanced frameworks such as PyTorch, TensorFlow, Hugging Face, ONNX Runtime, and LangChain, along with orchestration tools including Semantic Kernel, LangGraph, and CrewAI.
• Drive responsible integration of Large Language Models (LLMs) from OpenAI, Anthropic, Google Gemini, and Mistral, including deployment through Azure OpenAI Service or Vertex AI.
• Implement RAG architectures and manage vector databases (Pinecone, Weaviate, FAISS, Milvus) to power enterprise knowledge intelligence platforms.

Data Platform & Engineering Excellence

• Lead the evolution of the enterprise data landscape using modern platforms such as Databricks, Snowflake, Azure Synapse, and BigQuery.
• Oversee data engineering with Apache Airflow, dbt, and Prefect, ensuring performance, governance, and alignment with enterprise metadata standards (Collibra, Alation, Microsoft Purview).
• Drive adoption of Delta Lake, Iceberg, and Hudi to support scalable data lakehouse architectures.
• Ensure high‐quality, compliant, and reliable data foundations for ML and analytics workloads.

Cloud, Infrastructure & MLOps

• Champion multi‐cloud architecture across Azure, AWS, and GCP.
• Ensure resilient, secure, and cost‐efficient deployments using Docker, Kubernetes (AKS/EKS/GKE), and Terraform/Bicep.
• Lead enterprise MLOps capabilities using Azure ML, SageMaker, Vertex AI, MLflow, and Kubeflow, integrated with CI/CD (GitHub Actions, Azure DevOps, Jenkins, Argo CD).
• Oversee observability and monitoring using Prometheus, Grafana, ELK/EFK, and OpenTelemetry.

Enterprise Integration with .NET Ecosystems

• Guide the integration of AI/ML pipelines into enterprise‐scale .NET Core applications and service‐oriented architectures.
• Modernize legacy systems through microservices, REST/gRPC APIs, and event‐driven architectures (Azure Service Bus, Kafka).
• Implement secure DevSecOps practices—SonarQube, Checkmarx, Vault, Azure API Management—in line with enterprise compliance standards.

Intelligent Automation & Cognitive Services

• Drive end‐to‐end intelligent automation initiatives using Power Automate, Blue Prism, and Automation Anywhere.
• Integrate cognitive services (Azure Cognitive Services, AWS Comprehend, Form Recognizer, Speech/Translation APIs) to enhance workflow intelligence.
• Lead enterprise process mining using Celonis, Power BI Process Mining, and ProcessGold.

Analytics, BI & Decision Intelligence

• Oversee integration of analytics and AI capabilities to deliver measurable business impact.
• Advance analytics maturity using Power BI, Looker, and Azure Analysis Services.
• Promote predictive and optimisation modelling using PyCaret, Prophet, and Optuna to strengthen data‐driven decision‐making.

Security, Compliance & Responsible AI

• Ensure alignment with enterprise security frameworks (SOC2, ISO27001, NIST).
• Oversee identity and access management via Azure AD, OAuth2, OpenID Connect, and enterprise IAM systems.
• Champion ethical AI practices, including bias detection, explainability, and responsible use frameworks such as the Azure Responsible AI Dashboard.

Leadership, Talent & Innovation

• Build and lead high‐performing global teams across data science, engineering, and automation.
• Foster a culture of innovation, continuous learning, and responsible experimentation.
• Engage with the broader AI ecosystem—including academia, hyperscalers, and startups—to identify emerging technologies and partnership opportunities.

Preferred Background

• Proven experience integrating Python‐based AI with enterprise .NET ecosystems.
• Deep expertise across multi‐cloud environments, data governance, and enterprise‐grade DevSecOps.
• Demonstrated success delivering large‐scale transformation programs with measurable ROI.
• Strong executive presence with exceptional communication and stakeholder management skills.