Lead AI Platform Engineer

Overview Job Purpose We are on a mission as a team. We are problem solvers and partners, always starting with our customers to solve their challenges and create opportunities. Our start-up roots keep us nimble, flexible, and moving fast. We take ownership and make decisions. We all work for one company and work together to drive growth across the business. We engage in robust debates to find the best path, and then we move forward as one team. We take pride in what we do, acting with integrity and passion, so that our customers can perform better. We are experts and enthusiasts - combining ever-expanding knowledge with leading technology to consistently deliver results, solutions and opportunities for our customers and stakeholders. Every day we work toward transforming global markets. The AI Platform Engineering Lead drives the AI Platform Operations team, guiding platform strategy, governance, and stakeholder engagement. They align technical execution with business goals, ensuring cost-effective, secure, and scalable AI/ML solutions. The lead defines the 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. They establish design patterns and best practices that span LLM, MCP, and agentic capabilities, ensuring the platform scales securely and operates with consistency across the enterprise. The lead collaborates across teams to set security standards, manage resources, maintain compliance, and align platform capabilities with enterprise architecture standards. Responsibilities Define platform strategy, roadmap, and capability evolutionEstablish governance frameworks, policies, and exception processesManage team budget, CapEx planning, and vendor relationshipsBuild and lead the AI Platform Operations teamDefine the architecture, standards, and governance for AI/ML infrastructure, including GPU cluster design, compute resource planning, security controls, and observability across the platformDrive the strategy, standards, and governance for AI-enabled workflow automation across LLM, MCP, and agentic capabilities, ensuring the platform scales securely and operates with consistency across the enterpriseDefine the architecture and design standards for vector store infrastructure supporting RAG pipelines, agent memory, and semantic search across the enterpriseEstablish design patterns and best practices for RAG workflow implementation, including ingestion strategies, chunking approaches, embedding model selection, and retrieval optimizationArchitect agent memory frameworks, defining standards for short-term context, long-term persistent memory, and episodic memory patterns across AI platform workloadsDrive the architecture and governance of Agentic AI systems, including multi-agent orchestration design and tool-use pipeline standardsDefine the strategy and architecture for hosting and managing MCP servers across the platform, including deployment topology, security boundaries, and integration standardsEstablish governance frameworks and policies for MCP server lifecycle management, versioning, and access controlEvaluate and select MCP server tooling and vendors; manage relationships and roadmap alignmentServe as executive liaison for platform mattersOwn major incident management and executive communicationDrive continuous improvement and platform maturity initiativesAlign platform capabilities with enterprise architecture standardsRespond to and assist in production operations in a 24/7 environmentProvide technical analysis, resolve problems, and propose solutionsProvide support to, and coordinate with, developers, operations staff, release engineers, and end-usersEducate and mentor team members and operations staff Knowledge And Experience 8+ years in IT infrastructure or platform engineering roles3+ years in technical leadership or management positions1+ years hands-on experience with Kubernetes in productionDirect experience with GPU infrastructure (NVIDIA preferred)2+ years experience using CUDA1+ years experience using MCPs2+ years experience with vector databases and embedding infrastructure2+ years experience with RAG pipeline design and deployment2+ years experience with agent memory patterns (in-context, external stores, retrieval-augmented memory)1+ years experience with agentic AI systems using orchestration frameworks2+ years experience with semantic search, embedding models, and ANN search techniques3+ years working with workflow/orchestrion automation toolsExperience managing teams of 5+ technical staffDemonstrated success in vendor management and contract negotiationStrong executive communication and presentation skillsUnderstanding of AI/ML workloads and infrastructure requirementsExperience with enterprise monitoring and observability toolsAbility to work in a service-oriented team environmentProject Management, organization, and time managementCustomer focused, and dedicated to the best possible user experienceCommunicate effectively with both technical and business resourcesFluent speaking, reading, and writing in English Illinois Base Salary Range The expected base salary for this role, if located in Illinois, is between $133,900 - 154,500 USD.  The base salary range does not include Intercontinental Exchange’s incentive compensation.  While we provide this range as general guidance, at ICE we compensate employees based on the skillset and experience of the individual. Regular full-time ICE employees are eligible for a suite of competitive employee benefits, including healthcare coverage (medical, dental and vision), a 401(k) plan, life insurance, time off, and paid leave for qualifying circumstances. New York Base Salary Range The expected base salary for this role, if located in New York, is between $149,400 - 180,000 USD.  The base salary range does not include Intercontinental Exchange’s incentive compensation.  While we provide this range as general guidance, at ICE we compensate employees based on the skillset and experience of the individual. Regular full-time ICE employees are eligible for a suite of competitive employee benefits, including healthcare coverage (medical, dental and vision), a 401(k) plan, life insurance, time off, and paid leave for qualifying circumstances. California Base Salary Range The expected base salary for this role, if located in California, is between $149,400 - 180,000 USD.  The base salary range does not include Intercontinental Exchange’s incentive compensation.  While we provide this range as general guidance, at ICE we compensate employees based on the skillset and experience of the individual. Regular full-time ICE employees are eligible for a suite of competitive employee benefits, including healthcare coverage (medical, dental and vision), a 401(k) plan, life insurance, time off, and paid leave for qualifying circumstances. Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.