Description

You will define and build the enterprise AI technical vision.

This role is hybrid.

Responsibilities

• Define enterprise AI reference architectures supporting rapid experimentation, scalable deployment, and maintainability.
• Design end-to-end AI solutions covering data ingestion, model development, deployment, and monitoring.
• Architect data ecosystems providing high-quality, governed data for all AI/ML workloads.
• Design MLOps pipelines enabling continuous integration, delivery, and monitoring of AI models at scale.
• Embed governance, security, and compliance requirements into AI architecture from the initial design phase.

Required Skills

• 10-15 years of overall IT experience.
• Minimum 8+ years in data engineering, AI/ML, and solution architecture.
• 5+ years experience designing and delivering enterprise-level solutions.
• Hands-on experience with Azure ML, Synapse, Databricks, AWS, and GCP.
• Experience designing and implementing MLOps frameworks for continuous model delivery.
• Proficiency in architecting cloud-native AI platforms across hybrid environments.
• Ability to translate complex business requirements into understandable technical architectures.
• Familiarity with embedding responsible AI principles, security, and lineage tracking.

Preferred Skills

• Proven ability to design production-grade AI architectures with measurable business impact.
• Deep expertise in feature stores, model registries, and versioning frameworks.
• Experience leading technical teams and influencing enterprise architecture decisions.

Key Skills

Education

Bachelor's degree