Lead Engineer, Platform Engineering - AI

Intercontinental Exchange Holdings, Inc.•Pleasanton, CA

2d•$133,900 - $180,000•Onsite

About The Position

The AI Platform Engineering Lead drives the AI Platform Operations team and guides platform strategy, governance, and stakeholder engagement. The role aligns technical execution with business goals to ensure cost-effective, secure, and scalable AI/ML solutions. It defines architecture, standards, and governance across AI/ML infrastructure, workflow automation, and agentic AI capabilities, including RAG pipelines, vector store infrastructure, agent memory frameworks, and MCP server strategy. The lead establishes design patterns and best practices spanning LLM, MCP, and agentic capabilities so the platform scales securely and operates consistently across the enterprise. The role collaborates across teams on security standards, resource management, compliance, and alignment with enterprise architecture standards. The position also leads the AI Platform Operations team, manages its budget and vendor relationships, serves as an executive liaison, and owns major incident management and executive communication. It supports production operations in a 24/7 environment and coordinates with developers, operations staff, release engineers, and end-users.

Requirements

Bachelor's degree in an engineering discipline or equivalent experience in Systems Engineering or Development.
8+ years in IT infrastructure or platform engineering roles.
3+ years in technical leadership or management positions.
1+ years of hands-on experience with Kubernetes in production.
Direct experience with GPU infrastructure; NVIDIA preferred.
2+ years of experience using CUDA.
1+ years of experience using MCPs.
2+ years of experience with vector databases and embedding infrastructure.
2+ years of experience designing and deploying RAG pipelines.
2+ years of experience with agent memory patterns, including in-context, external stores, and retrieval-augmented memory.
1+ years of experience with agentic AI systems using orchestration frameworks.
2+ years of experience with semantic search, embedding models, and ANN search techniques.
3+ years working with workflow/orchestration automation tools.
Experience managing teams of 5+ technical staff.
Demonstrated success in vendor management and contract negotiation.
Strong executive communication and presentation skills.
Understanding of AI/ML workloads and infrastructure requirements.
Experience with enterprise monitoring and observability tools.
Ability to work in a service-oriented team environment.
Project management, organization, and time management skills.
Customer-focused approach and dedication to the best possible user experience.
Ability to communicate effectively with technical and business resources.
Fluent speaking, reading, and writing in English.

Responsibilities

Define the platform strategy, roadmap, and capability evolution.
Establish governance frameworks, policies, and exception processes.
Manage the team budget, CapEx planning, and vendor relationships.
Build and lead the AI Platform Operations team.
Define architecture, standards, and governance for AI/ML infrastructure, including GPU cluster design, compute resource planning, security controls, and platform observability.
Drive strategy, standards, and governance for AI-enabled workflow automation across LLM, MCP, and agentic capabilities.
Define architecture and design standards for vector store infrastructure supporting enterprise RAG pipelines, agent memory, and semantic search.
Establish design patterns and best practices for RAG workflows, including ingestion strategies, chunking, embedding model selection, and retrieval optimization.
Architect agent memory frameworks and define standards for short-term context, long-term persistent memory, and episodic memory patterns.
Drive architecture and governance of agentic AI systems, including multi-agent orchestration and tool-use pipeline standards.
Define strategy and architecture for hosting and managing MCP servers, including deployment topology, security boundaries, and integration standards.
Establish governance frameworks and policies for MCP server lifecycle management, versioning, and access control.
Evaluate and select MCP server tooling and vendors; manage relationships and roadmap alignment.
Serve as executive liaison for platform matters.
Own major incident management and executive communication.
Drive continuous improvement and platform maturity initiatives.
Align platform capabilities with enterprise architecture standards.
Respond to and assist with production operations in a 24/7 environment.
Provide technical analysis, resolve problems, and propose solutions.
Support and coordinate with developers, operations staff, release engineers, and end-users.
Educate and mentor team members and operations staff.