ETIC, AI Architect - Director level
Core
Define and execute enterprise strategy for AI, Machine Learning, and Automation, blending technical excellence with strategic leadership to deliver scalable intelligent systems.
Role type
Director-level AI Architect (Strategy & Technical Leadership)
Builds
Scalable, secure, value-generating intelligent systems and enterprise AI/automation capabilities.
Domain
Technology / Enterprise AI & Intelligent Automation
Deliverable
production ML models | product features | infrastructure
Required skills
Strategic AI governance, Python, .NET, cloud-native architectures, LLM orchestration (Semantic Kernel, LangGraph, CrewAI, LangChain, AutoGen, LlamaIndex), RAG architectures, vector databases, multi-cloud strategy (Azure, AWS, GCP), MLOps (Azure ML, SageMaker, Vertex AI, MLflow, Kubeflow), data platform leadership (Databricks, Snowflake, Azure Synapse, AWS Glue/Redshift, BigQuery), data engineering (Apache Airflow, dbt, Prefect), intelligent automation (Power Automate, Blue Prism, Automation Anywhere), process mining (Celonis, Power BI Process Mining, ProcessGold), enterprise security frameworks (SOC2, ISO27001, NIST), IAM (Azure AD, OAuth2, OpenID Connect), responsible AI implementation.
Preferred skills
Consulting leadership experience, enterprise transformation delivery, measurable ROI generation, external ecosystem engagement.
Technologies
Semantic Kernel, LangGraph, CrewAI, LangChain, AutoGen, LlamaIndex, Azure OpenAI, Amazon Bedrock, Vertex AI, Databricks, Snowflake, Azure Synapse, AWS Glue, Redshift, BigQuery, Apache Airflow, dbt, Prefect, Collibra, Alation, Microsoft Purview, Azure ML, SageMaker, Vertex AI, MLflow, Kubeflow, Power Automate, Blue Prism, Automation Anywhere, Azure Cognitive Services, AWS Comprehend, Celonis, Power BI, Azure Responsible AI Dashboard.
Responsibilities
Define global AI strategy aligned with digital transformation; establish technical governance for AI ethics and model transparency; partner with C-suite to embed AI capabilities at scale; lead evolution of enterprise data estate and data engineering pipelines; champion multi-cloud architecture and MLOps initiatives; drive end-to-end intelligent automation and cognitive services integration; ensure alignment with enterprise security standards and responsible AI frameworks; build and lead global teams in data science and engineering.
Seniority
Director, strategic leadership with hands-on technical architecture
