Engineer, Platform Engineering - AI

• We are problem solvers and partners, always starting with our customers to solve their challenges and create opportunities.
• The AI Platform Engineer is responsible for the technical implementation, maintenance, and optimization of AI/ML infrastructure.

About Intercontinental Exchange, Inc.

• Job Purpose We are on a mission as a team.
• 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.

Responsibilities

• This hands-on role focuses on GPU cluster deployment, container image management, platform tooling development, and deep technical troubleshooting.
• In addition, the engineer deploys and maintains AI-enabled workflow automation tools across LLM, MCP, and agentic capabilities, ensuring these systems operate efficiently and securely within a containerized architecture.
• This includes deploying and maintaining vector store infrastructure, implementing end-to-end RAG workflows, tuning agent memory systems, and hosting and managing MCP servers.
• The engineer also deploys and operates Agentic AI systems, including multi-agent orchestration frameworks and tool-use pipelines.
• The engineer serves as a core technical contributor on the AI Platform Operations team, translating architectural decisions into working infrastructure and enabling advanced, automated workflows across the platform.
• Deploy, configure, and maintain GPU clusters and associated infrastructure
• Designing, building, and maintaining the workflow automation platform that uses AI capabilities (LLM/MCP/Agentic capabilities)

NVIDIA driver versions, CUDA toolkits, and container runtimes

• Build and maintain approved container images with ML frameworks (PyTorch, TensorFlow, etc.) Implement monitoring, alerting, and observability for GPU infrastructure
• Deploy and maintain vector store infrastructure for RAG pipelines, agent memory, and semantic search
• Implement and maintain end-to-end RAG workflows, including document ingestion, chunking, embedding generation, and retrieval optimization
• Maintain and tune agent memory systems, including short-term context windows, long-term persistent memory stores, and episodic memory retrieval patterns

Deploy, operate, and maintain

• Agentic AI systems, including multi-agent orchestration frameworks and tool-use pipelines
• Deploy, host, and maintain MCP servers within the containerized platform infrastructure
• MCP server configurations, versioning, access controls, and integration with agentic workflows
• MCP server health, performance, and availability; respond to incidents and perform root cause analysis
• Develop automation and tooling to improve platform reliability and efficiency
• Provide L2/L3 technical support and vendor escalation for complex issues
• Implement security controls including network policies, RBAC, and secrets management
• Execute change requests and maintain technical documentation
• Respond to and assist in production operations in a 24/7 environment
• Provide technical analysis, resolve problems, and propose solutions
• Provide support to, and coordinate with, developers, operations staff, release engineers, and end-users

Educate and mentor team members and operations staff

• Participate in a weekly on-call rotation for after-hours support
• Customer focused, and dedicated to the best possible user experience
• Communicate effectively with both technical and business resources
• Fluent speaking, reading, and writing in English Desired Knowledge and Experience 1+ years of experience with AI developer toolkits (NVIDIA drivers, CUDA, cuDNN, and NCCL) 1+ years of experience with Run:AI, NVIDIA AI Enterprise, or DGX systems 1+ years of experience with n8n 1+ years of experience with GitHub Actions #LI-SH3 #LI-ONSITE ---------- Intercontinental Exchange, Inc. is an Equal Opportunity Employer.

Requirements

• 3+ years in infrastructure engineering, systems administration, or DevOps 3+ years in scripting and automation skills (Python, Ansible, GitOps) 3+ years hands-on experience with Kubernetes in production 2+ years experience with Linux administration
• Direct experience with GPU infrastructure (NVIDIA preferred) 1+ years experience using CUDA 1+ years experience using MCPs 1+ years experience with vector databases and embedding infrastructure 1+ years experience with RAG pipeline design and deployment 1+ years experience with agent memory patterns (in-context, external stores, retrieval-augmented memory) 1+ years experience with agentic AI systems using orchestration frameworks 1+ years experience with semantic search, embedding models, and ANN search techniques 1+ years working with workflow/orchestrion automation tools Experience with enterprise monitoring and observability tools
• Ability to work in a service-oriented team environment
• Project Management, organization, and time management

Preferred

• Knowledge and Experience Bachelor's degree preferred.

All qualified applicants will receive consideration for employment without regard to legally protected characteristics.