ML / AI Platform Architect

Key Responsibilities

• Design and own the end-to-end architecture for enterprise AI/ML platforms.
• Build and operationalize Feature Store and Model Catalog capabilities to support reusable feature engineering, model versioning, and self-service ML adoption.
• Develop and manage Agentic AI platform infrastructure, including agent runtimes, orchestration frameworks, tool integrations, and agent lifecycle management.
• Establish and maintain Agent Catalog capabilities to enable deployment, discovery, monitoring, and governance of AI agents.
• Design and implement AI governance controls, including access management, policy enforcement, audit logging, monitoring, and observability.
• Develop MLOps pipelines and cloud-native deployment frameworks to support scalable AI/ML workloads.
• Collaborate with Data Science, Engineering, Security, and Business teams to deliver enterprise AI solutions.

Required Skills

• 7+ years of experience in AI/ML platform engineering, cloud architecture, or MLOps.
• Strong experience with AI/ML platforms, Feature Stores, Model Registries/Catalogs, and MLOps frameworks.
• Hands-on experience with Agentic AI, LLM platforms, and orchestration frameworks.
• Proficiency in Python, APIs, Kubernetes, Docker, and cloud platforms (Azure preferred).
• Knowledge of AI governance, security, compliance, and observability best practices.
• Strong problem-solving, architecture, and communication skills.