Jeremy Eder

About Jeremy Eder

I build platforms that make AI work for engineers.My current focus is ambient-code.ai [1], a platform for AI-assisted software development, with open source tools at github.com/ambient-code [2]. The differentiator is an async work pattern that schedules codegen tasks on Kubernetes like any other HPC job. AgentReady [3] evaluates research-backed attributes that determine how well a codebase works with AI coding agents.At Red Hat, I\'m a Distinguished Engineer reporting to the VP of AI Engineering. In 2025, I led the launch of llm-d [4], a distributed inferencing project co-created by Red Hat and Google for Kubernetes. This was the headline feature of Red Hat OpenShift AI 3.0. I led a globally distributed team of 100+ researchers and engineers from concept to Red Hat Summit stage in about 7 weeks.I served on the PyTorch Governing Board and Technical Advisory Council, representing Red Hat and IBM. I bootstrapped Red Hat\'s PyTorch team from scratch and we became a top 10 contributor.Earlier, I led the launch of Red Hat OpenShift Service on AWS (ROSA)[5], the first non-AWS service listed directly in the AWS console. Before that, I made Kubernetes suitable for performance-sensitive workloads, publishing the first public 2048 node cluster benchmarks [6] in the CNCF and bootstrapping the Kubernetes Resource Management Working Group [7] that enabled GPU support on Kubernetes.Before containers, I worked in financial services on extreme low-latency architecture, helping launch the International Securities Exchange trading platform and supporting Citadel Securities, Chicago Mercantile Exchange, and Jump Trading.I hold multiple patents, completed MIT Sloan\'s Executive Certificate in Strategy and Innovation in 2022, and received Red Hat\'s Chairman\'s Award in 2014.Open to conversations about AI infrastructure, generative AI for coding, agentic development, and all things next.[1] https://ambient-code.ai[2] https://github.com/ambient-code[3] https://github.com/ambient-code/agentready[4] https://llm-d.ai[5] https://aws.amazon.com/rosa[6] https://kubernetes.io/blog/2017/09/introducing-resource-management-working

Experience

1. Distinguished Engineer and Chief Ai Ml Strategist at Red Hat

   Red Hat

   Aug 2023 — Present · Raleigh, NC, US

   I work for the VP of AI Engineering on our most cutting edge strategies and innovative projects. I focus on bringing these to market in the optimal order while navigating the complexities of partnerships, open source technology, law, ethics, and competition. In this role I continued to add a variety of experiences in M&A (qualifying technical projects) and working directly with researchers and product teams to manage the flow of innovation.Most importantly, I approach the majority of my work through the system dynamics approach. https://en.wikipedia.org/wiki/System_dynamics and believe a holistic, systems approach to problem solving delivers the most impactful and durable results. Not enough people prioritize the benefits of a systems-level fix vs a quick fix.In this role, I* Represent Red Hat and IBM on the PyTorch Governing Board and Technical Advisory Council: https://docs.google.com/presentation/d/1cE8ZvRK21cPG-CP9SOzWsvlWMtddLtUz/edit#slide=id.g31f07f26c07_0_1* Lead a cross-functional steering committee of senior engineering and product executives to accelerate AI innovation between research and product. My role is to systematically quantify the impact of each advancement, and work with researchers to refine our projects.* Spearheaded the creation of Red Hat’s Open Source AI strategy, aligning engineering, research, and product development with the broader AI ecosystem. I still have the whiteboard picture.* Led Red Hat’s transition to Kubeflow, enabling scalable and reproducible ML workflows on Kubernetes.

Education

• Massachusetts Institute of Technology

  Executive Certificate in Strategy and Innovation, Sloan School of Management

• Rochester Institute of Technology

  Computer Engineering

Skills

• Redhat
• Enterprise Software
• Apache
• Linux
• Cloud Computing
• Red Hat Linux
• Virtualization
• Bash
• Rhel