Note: The job is a remote job and is open to candidates in USA. GMI Cloud is an AI-native infrastructure company delivering GPU compute, inference services, and infrastructure for AI agents. The Technical Program Manager will coordinate cross-functional infrastructure engineering programs, manage roadmaps and delivery, support architecture and reliability initiatives, and communicate priorities, risks, and progress across engineering teams.

Responsibilities

• Lead end-to-end technical programs across infrastructure domains (GPU orchestration, cluster management, networking, storage, telemetry, provisioning pipelines)
• Align program scope, milestones, dependencies, success metrics, and delivery timelines
• Drive program rituals: kickoff, sprint alignment, risk reviews, and postmortems
• Proactively support the Head of Infrastructure in setting priorities, sequencing work, meeting coordination, and driving execution across teams
• Serve as the coordinator within infrastructure organization: SRE, Platform Developers, Architects
• Proactively surface and manage dependencies, blockers, and risks across teams
• Communicate program status, trade-offs, and timelines to the Head of Infrastructure and other stakeholders
• Manage roadmaps and release plans for multi-team infrastructure initiatives; work directly with the Head of Infrastructure to align execution with strategic goals and adjust priorities as needed
• Implement scalable program management practices (OKRs, milestones, RACI, risk logs, SLAs)
• Ensure engineering deliverables meet performance, reliability, security, and cost targets
• Maintain a strong technical understanding of GPU infrastructure, ensure architecture and program decisions align with NVIDIA NCP (NVIDIA Cloud Platform) reference architecture and best practices where applicable — including hardware configurations, networking/topology, telemetry, and security recommendations
• Facilitate architecture reviews and help translate architecture into executable work for platform engineers and SREs
• Coordinate SRE-driven reliability initiatives (SLOs, incident response playbooks, SOP)
• Help prioritize reliability work vs. feature work and plan operational runbooks, testing, and rollout strategies
• Define and track key KPIs (uptime, mean time to recovery, provisioning latency)
• Use data to drive prioritization and continuous improvement cycles

Skills

• Bachelor's degree in Computer Science, Engineering, or equivalent experience
• 5+ years of technical program management experience at an infrastructure- or platform-oriented organization (start-up experience strongly preferred)
• Strong technical background with hands-on familiarity in at least one of: GPU compute stacks, Kubernetes, cluster orchestration, or cloud infrastructure
• Demonstrated experience coordinating across SRE, platform engineering, and architecture teams to deliver complex multi-quarter programs
• Proven track record of delivering projects with multiple engineering teams and external dependencies
• Excellent written and verbal communication—able to summarize technical trade-offs and program status for executive stakeholders
• Strong organizational skills: roadmaps, dependency mapping, risk management, and prioritization
• Data-driven: experience defining, monitoring, and improving KPIs and SLAs
• Comfortable with ambiguity and rapid change in a start-up environment
• Experience with incident management, postmortems, and on-call processes
• Direct experience with GPU orchestration tools (Device Plugin, MIG, NCCL, CUDA drivers), Kubernetes GPU scheduling frameworks, or custom scheduler implementations
• Experience with on-prem/cloud deployments
• Familiarity with infrastructure-as-code, CI/CD, and observability tooling (Prometheus, Grafana, OpenTelemetry)
• Prior experience at a GPU-focused company, ML infrastructure team, or HPC environment

Company Overview

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