Teams at Red Hat

Lead the design, optimization, and production deployment of high-performance LLM inference systems using vLLM, CUDA, Triton, C++, and Python. Improve GPU utilization, latency, throughput, scalability, and cost through kernel optimization, quantization, batching, memory management, distributed inference, and profiling. Contribute to upstream open-source projects, establish engineering standards, review performance-critical code, and guide research-driven serving improvements.

Provides deep technical sales support for Red Hat Lightwell, helping customers adopt trusted software supply chain practices. Leads technical discussions, proofs of concept, build integrations, dependency management, artifact signing, SBOMs, attestation, pipeline enforcement, and vulnerability remediation. Partners with sales, engineering, consulting, customer success, and product teams; delivers workshops, enablement, mentoring, public speaking, and market feedback. Requires hands-on experience with enterprise builds, artifact repositories, CI/CD, DevSecOps, and software supply chain security.

Conduct interviews with partners, solution architects, and sales teams to identify enterprise AI use cases. Analyze findings, map customer needs to Red Hat’s AI platform and partner ecosystem, identify go-to-market opportunities, and present strategic recommendations to AI Ecosystem leadership.