Director of AI Engineering in Tech Catalyst
Listed on 2026-02-07
-
IT/Tech
AI Engineer, Data Engineer
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 ResponsibilitiesStrategic 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
- 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, Tensor Flow, Hugging Face, ONNX Runtime, and Lang Chain, integrating orchestration tools like Semantic Kernel, Lang Graph, 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 Big Query.
- 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, Sage Maker, Vertex AI, MLflow, and Kubeflow, with continuous integration pipelines (Git Hub Actions, Azure Dev Ops, Jenkins, Argo CD).
- Oversee monitoring and observability using Prometheus, Grafana, ELK/EFK, and Open Telemetry.
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 Dev Sec Ops practices—Sonar Qube, 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 Process Gold.
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…
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