Description

Define and lead the architecture of scalable AI/ML and agentic systems across the global product portfolio.

This role is remote.

Responsibilities

• Define reference architecture for LLM, ML, and agent-based systems across products.
• Design high-availability, low-latency inference platforms for global scale.
• Architect multi-step, reasoning-driven agent systems and orchestration patterns for tool use.
• Lead implementation and governance of Model Context Protocol (MCP) servers.
• Set best practices for MLOps, CI/CD, observability, and system reliability.

Required Skills

• 10+ years experience building production-grade ML systems at scale.
• Strong LLM, Generative AI, and RAG deployment experience.
• Expertise designing systems in cloud environments (AWS, Azure, or GCP).
• Hands-on work with Kubernetes, containerization, and scalable inference systems.
• Experience designing agentic systems and tool orchestration frameworks.
• Ability to implement and govern MCP servers or structured architectures.
• Strong Python background.

Preferred Skills

• Experience embedding Responsible AI principles across platform architecture.
• Mentoring senior engineers and influencing technical direction across teams.

Key Skills

Education

Any Graduate