Job Description

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

15+ years in technology or consulting leadership with significant experience delivering enterprise AI, data, and automation transformations. 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.