Hemang Shishir

About Hemang Shishir

Technology executive and AI platform architect with 20+ years of experience building and scaling large-scale distributed systems, leading high-performing engineering organizations, and driving multimillion-dollar revenue growth. My career spans enterprise cloud platforms, AI infrastructure, and customer-facing technical strategy—combining deep hands-on architecture expertise with executive-level leadership and market vision.Today, I focus on architecting and operationalizing production-grade AI systems at scale. I partner with Fortune 500 organizations—especially in Financial Services, Healthcare, and Public Sector—to design and operationalize Model-as-a-Service and GPU-as-a-Service platforms on enterprise Kubernetes. My work spans high-throughput LLM inference (vLLM, distributed inference/LLM-D), GPU optimization, model customization, fine-tuning, validation, and performance engineering—helping customers move from AI experimentation to scalable, governed AI in production.I have led complex AI platform engagements contributing to $XXM+ in revenue, driving executive architecture strategy, competitive bake-offs, POCs, and large-scale deployments. I collaborate closely with product and engineering teams to influence roadmap direction based on real-world enterprise AI patterns and scalability demands.Beyond delivery, I’ve built and led teams of 50+ engineers and managers, managed large vendor ecosystems, and driven double-digit growth initiatives. I am a frequent invited speaker at AI conferences and partner events across North America, sharing practical insights on GPUaaS, MaaS, agentic workflows, model optimization, and enterprise AI transformation.

Experience

1. Principal Specialist Ai Architect

   Red Hat

   Apr 2024 — Present · Seattle, WA, US

   Strategic AI platform leader driving enterprise AI adoption across key North American accounts, partnering with Fortune 500 customers—especially in Financial Services—to design, deploy, and scale production-grade AI systems- Influenced and supported $XXM+ in AI platform revenue by leading technical strategy, architecture, and execution across high-value enterprise accounts- Architected and delivered end-to-end Model-as-a-Service (MaaS) and GPU-as-a-Service (GPUaaS) platforms on enterprise Kubernetes (OpenShift), enabling scalable and governed AI workloads- Deep hands-on expertise in vLLM, distributed inference (LLM-D), high-throughput model serving, GPU optimization, and performance tuning, driving measurable improvements in latency, throughput, and infrastructure efficiency- Led model customization initiatives including fine-tuning, domain adaptation, validation, and performance benchmarking for regulated industry use cases- Designed and executed advanced data pipelines, ML pipelines, distributed training, and inference architectures in collaboration with Red Hat engineering and AI business units- Drove pre- and post-sales technical strategy: POCs, competitive bake-offs, executive architecture sessions, internal sprints, and vertical AI solution development- Partnered closely with HPE, Cisco, and strategic ecosystem players on joint AI initiatives, reference architectures, and customer engagements- Invited speaker at Cisco, HPE, and major AI conferences across North America, delivering thought leadership on GPUaaS, MaaS, agentic workflows, model optimization, and enterprise AI operationalization- Led AI roadshows and technical workshops for executives, data scientists, and platform teams—bridging business value with deep technical implementation- Served as a market feedback conduit to product and engineering, influencing roadmap direction based on real-world enterprise AI deployments.

Education

• Florida Institute of Technology

  Bachelor of Engineering - BE, Computer Engineering