Technical Program Manager (Engineering) - Remote

Overview

Deepgram is the leading voice AI platform for developers building speech-to-text (STT), text-to-speech (TTS) and full speech-to-speech (STS) offerings. 200,000+ developers build with Deepgram’s voice-native foundational models – accessed through APIs or as self-managed software – due to our unmatched accuracy, latency and pricing. Customers include software companies building voice products, co-sell partners working with large enterprises, and enterprises solving internal voice AI use cases. The company ended 2024 cash-flow positive with 400+ enterprise customers, 3.3x annual usage growth across the past 4 years, over 50,000 years of audio processed and over 1 trillion words transcribed. There is no organization in the world that understands voice better than Deepgram.

Deepgram is seeking a Technical Program Manager (Engineering) to drive execution across complex, cross-functional programs involving both software and hardware. In this role, you’ll work closely with our engineering and research teams to manage large-scale, technically demanding initiatives—from inception through delivery.

In Short

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

Requirements

• 5+ years of program management experience leading large, cross-functional initiatives.
• Strong technical acumen—bonus if you’ve been an engineer or worked closely with applied-ML teams.
• Experience coordinating programs that touch both hardware and software domains.
• 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.

Benefits

• 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).