Senior Technical Program Manager (engineering)

Deepgram Deepgram · AI Frontier · United States · Remote · Engineering

Senior Technical Program Manager (Engineering) at Deepgram, a Voice AI platform company. This role will drive the end-to-end delivery of complex, cross-functional technical programs involving software, hardware, and research efforts. The TPM will define workstreams, set milestones, coordinate execution, identify and resolve bottlenecks, and dive deep into technical topics. The role requires strong technical acumen, experience with AI/ML workloads and infrastructure, and the ability to manage programs in high-growth environments. The company emphasizes an AI-first mindset and expects active use and experimentation with AI tools.

What you'd actually do

  1. Own the end-to-end delivery of technical programs, many of which span hardware, software, and research efforts
  2. Define workstreams, set milestones, and coordinate execution across multiple teams and functions
  3. Serve as the connective tissue between engineering, research, product, and operations to ensure aligned priorities and timelines
  4. Proactively identify and resolve bottlenecks, trade-offs, and interdependencies
  5. Dive deep into technical topics to ensure risks are understood and addressed early
  6. Build lightweight processes and tooling to help teams scale sustainably

Skills

Required

  • 5+ years of program management experience leading large, cross-functional initiatives
  • Strong technical acumen
  • Experience coordinating programs that touch both hardware and software domains
  • AI forward program management practices and processes
  • Proven ability to thrive in high-growth or startup environments
  • Comfortable navigating ambiguity and helping others do the same
  • Excellent communication and stakeholder management skills

Nice to have

  • been an engineer or worked closely with applied-ML teams
  • Familiarity with AI/ML workloads and their infrastructure requirements
  • Knowledge of cost optimization for cloud and on-premise infrastructure
  • Experience with multi-region, multi-cloud infrastructure deployment
  • Background in performance optimization for distributed systems
  • Experience with software-defined infrastructure and networking
  • Certification and/or hands on experience with relevant cloud platforms (AWS, GCP, Azure)
  • Experience with software-defined infrastructure and networking

What the JD emphasized

  • AI forward program management practices and processes

Other signals

  • drive execution across complex, cross-functional programs involving both software and hardware
  • manage large-scale, technically demanding initiatives—from inception through delivery
  • partner with researchers, engineers, and business stakeholders to align teams and outcomes
  • build lightweight processes and tooling to help teams scale sustainably
  • AI infrastructure
  • distributed systems for performance and cost
  • GPU infrastructure, and frontier research in ML architecture
  • intersection of humans and AI/ML systems
  • AI forward program management practices and processes