Job Specifications
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.