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Majestic Labs AI

Software Technical Project Manager

Posted 16 Days Ago
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In-Office
Los Altos, CA, USA
Expert/Leader
In-Office
Los Altos, CA, USA
Expert/Leader
Lead end-to-end technical programs across compiler, kernel, runtime, hardware integration, and data center deployment. Translate system architectures into schedules, manage cross-team dependencies and suppliers, run planning ceremonies, surface risks, and maintain project documentation and roadmaps to deliver production-ready server solutions.
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Description

About Us:

We’re a fast-moving AI startup building next-generation infrastructure for the world’s most demanding AI workloads. Our mission is to accelerate the future of intelligence by delivering cutting-edge server solutions optimized for large-scale inference. Backed by top-tier investors and led by industry veterans, we’re scaling rapidly and looking for an experienced program manager to organize and drive our most complex product builds.

About the Role

We're seeking an experienced Technical Project Manager with operational expertise to lead large-scale, cross-functional engineering programs, unblocking development bottlenecks, mitigating risks, and translating complex system architecture into actionable timelines for internal teams and ODM partners. This is a hybrid role that bridges technical depth with operational rigor — you'll manage complex, multi-disciplinary projects involving hardware design, procurement, deployment, network architecture, and preparation to scale. This role encompasses coordinating multiple suppliers and manufacturing partners, optimizing production workflows, and ensuring we deliver servers reliably to meet customer commitments. You'll work closely with silicon, software and systems engineers, ML teams, as well as business and operations to ensure our products are robust, reliable, and production-ready.

Key Responsibilities

  • Own end-to-end program management for projects spanning compiler infrastructure (IR design, optimization passes, codegen), custom AI kernel development, and GPU runtime/scheduling systems
  • Partner closely with compiler engineers, kernel developers, and systems architects to build realistic roadmaps, break down complex technical work into sequenced milestones, and track progress against them
  • Identify and manage cross-team dependencies
  • Translate ambiguous technical goals into scoped, actionable project plans
  • Run planning ceremonies and surface technical risk early
  • Coordinate with hardware and silicon partners on integration timelines, driver dependencies, and co-design feedback loops
  • Maintain project documentation, architecture decision records, and technical roadmaps in collaboration with engineering leads
Requirements

Required Qualifications

•    10+ years in program/project management, including 5+ years leading technically complex, multi-stakeholder programs

•    Track record of managing multi-team technical programs with interdependent workstreams and hard performance/correctness requirements

•    Strong operational background: defining processes, metrics, and driving efficiency

•    Technical fluency in data center, networking, or compute infrastructure; able to engage deeply with engineers

•    Conceptual familiarity with AI compute, distributed training, or inference systems

•    Excellent written/verbal communication across technical and non-technical audiences

•    Proficiency with Jira, Asana, Monday.com, or similar; comfort with data/metrics dashboards

Preferred Qualifications

  • Software development experience with infrastructure projects like storage, OS, and hardware bring-up.
  • Experience managing or scaling data center operations, cloud infrastructure (AWS, GCP, Azure), or hyperscaler / on-premises server deployments
  • Background in DevOps, infrastructure engineering, or site reliability engineering (SRE)
  • Experience with AI/ML infrastructure, GPU clusters, or distributed computing systems
  • PMP, CAPM, or equivalent program management certification
  • Previous role in a high-growth tech or AI company

Skills & Attributes

  • Analytical, data-driven decision-making with a metric-driven mindset (dashboards, KPIs)
  • Comfortable with ambiguity; able to bring clarity and proactively manage risk and contingency
  • Strong stakeholder influence, collaborative leadership, and attention to both detail and big-picture outcomes

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