Description

You will design enterprise AI/ML architectures, connecting ML pipelines to production deployment workflows.

This role is remote.

Responsibilities

• Define and implement MLOps practices for training, evaluation, deployment, monitoring, and lifecycle management.
• Architect scalable AI systems that meet performance, reliability, and operational requirements in cloud environments.
• Lead technical design for AI-ready data architecture, including data modeling and governance alignment.
• Collaborate with engineering teams to operationalize AI infrastructure components and support GenAI/LLM use cases.

Required Skills

• 8-15 years of experience designing enterprise AI/ML architectures and production AI systems.
• Strong expertise in MLOps, including model lifecycle standardization, automation, and production operations.
• Proficiency in Google Cloud Platform (GCP) for designing and running scalable AI systems.
• Experience with end-to-end ML pipelines and AI deployment patterns for reliable release and operationalization.
• Knowledge of data architecture, data modeling, and ETL/ELT processes.
• Familiarity with vector database integration and LLM technologies.

Preferred Skills

• Experience with Agentic AI roles, multi-agent systems, and GenAI solutions.
• Background in enterprise data platforms and AI transformation initiatives.

Key Skills

Education

Any Graduate