Technical Program Manager

TensorWave•Las Vegas, NV

51d

About The Position

At TensorWave, we’re leading the charge in AI compute, building a versatile cloud platform that’s driving the next generation of AI innovation. We’re focused on creating a foundation that empowers cutting-edge advancements in intelligent computing, pushing the boundaries of what’s possible in the AI landscape. About the Role: TensorWave is seeking an experienced Technical Program Manager to drive the execution of complex AI infrastructure initiatives that power cutting-edge machine learning workloads. In this role, you'll be the connective tissue between engineering, product, and business teams, ensuring our AMD-powered AI platform delivers exceptional performance and reliability at scale. You'll own the end-to-end program lifecycle for critical infrastructure projects, from initial scoping through deployment and iteration, working at the intersection of hardware optimization, distributed systems, and ML operations.

Requirements

3+ years of technical program management experience in infrastructure, cloud platforms, or ML/AI systems
Strong technical background with ability to engage in architecture discussions around distributed systems, GPU computing, or ML frameworks
Proven track record of delivering complex, multi-quarter programs involving hardware and software components
Experience managing cross-functional initiatives with engineering, product, and business stakeholders
Experience with Jira and implementing Jira workflows to match team processes
Excellent written and verbal communication skills, with ability to tailor messaging for technical and non-technical audiences
Bachelor's degree in Computer Science, Engineering, or related technical field
Reside in, or are open to relocating to Las Vegas, NV.

Nice To Haves

Experience with AMD GPU architectures (ROCm, Instinct GPUs) or competitive platforms (NVIDIA CUDA, Google TPUs)
Background in ML infrastructure, model training/inference pipelines, or MLOps platforms
Prior experience at a high-growth startup or in a fast-paced infrastructure organization
Hands-on technical experience as a software engineer or systems engineer earlier in career
Familiarity with Kubernetes, distributed training frameworks (PyTorch, JAX), or AI workload orchestration

Responsibilities

Lead cross-functional programs spanning hardware deployment, software infrastructure, and ML platform development, ensuring alignment across engineering, product, and operations teams
Define program scope, objectives, and success metrics for AI infrastructure initiatives, from GPU cluster buildouts to inference optimization projects
Drive cross-functional roadmap planning and prioritization, balancing immediate customer needs with long-term platform scalability
Manage program timelines, dependencies, and resource allocation across multiple concurrent initiatives
Translate complex technical tradeoffs into clear business implications for executive leadership and external partners
Communicate program status, risks, and blockers through regular updates, maintaining transparency across the organization
Identify and mitigate technical and operational risks before they impact delivery timelines or system performance
Drive postmortems and retrospectives to capture learnings and continuously improve execution velocity