Jobs 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.

Software Engineering interns work with mentors and international teams to design, develop, maintain, debug, and enhance Red Hat products such as RHEL and OpenShift. Interns collaborate with Quality Engineering, Design, Product Management, and Documentation teams while learning technologies including Python, Golang, Ansible, OpenShift, and AI. The program provides professional development, networking, curriculum, and hands-on project experience.

Supports technical product marketing by creating demos, tutorials, blogs, labs, workflows, dashboards, and presentations for Red Hat products. Collaborates with product managers, engineers, and technical teams to explain complex capabilities clearly, analyze product or content data, explore customer use cases, and use AI tools to improve content creation and delivery.

Supports product management activities including gathering customer and stakeholder input, conducting competitive analysis, documenting and prioritizing requirements, epics, and user stories, and collaborating with engineering teams on software solutions. The intern works with mentors and global cross-functional teams while developing product, technical, analytical, and communication skills.

Research enterprise AI use cases through interviews with partners, solution architects, and field sales teams. Analyze qualitative and quantitative findings, identify AI adoption opportunities, map customer needs to Red Hat’s AI platform and partner ecosystem, and recommend partner engagement strategies. Present a final report with strategic recommendations to AI Ecosystem leadership.

Participates in Red Hat’s 10-month FASTER development program, building expertise in cloud, automation, AI, and enterprise solution architecture. Learns Red Hat technologies, shadows experienced architects, supports customer presentations, demonstrations, workshops, proof-of-value activities, and pilot projects. Engages customers to understand technical challenges, develops solutions, supports sales objectives, pursues certifications, and collaborates with internal teams and external customers. The role requires customer engagement, communication, presentation, problem-solving, self-directed learning, and willingness to travel.

Provides enterprise customers with technical and architectural guidance for Red Hat Enterprise Linux. Responsibilities include customer advocacy, product upgrades, technical reviews, incident management, troubleshooting, documentation, roadmap guidance, and cross-functional collaboration with engineering and support teams. The role manages customer relationships, supports infrastructure and application environments, and delivers proactive, relationship-based technical support. Occasional customer-site visits may be required.