Senior Technical Program Manager II - AI

Description

The company builds technology for public safety, pairing devices with cloud software.

This role sits between AI research, engineering, product management and hardware. You will guide AI work from first concept through model development, cloud and edge rollout, and ongoing tuning after launch.

You will lead major programs in generative AI workflows for report drafting and form completion, video search with automated redaction, and on-device edge vision and alerting.

You act as a strategic technical operator, reducing risk in complex ML systems, scaling internal delivery, and moving research into production environments where failure matters.

Candidates who do not meet every qualification are encouraged to apply.

Responsibilities

• Own multi-team AI programs from design and data collection through training, deployment and post-launch evaluation.
• Set strategy and roadmaps with AI scientists, ML engineers, product managers and executives, and keep delivery milestones aligned.
• Manage the technical dependencies between research, cloud microservices on AWS, Azure or GCP, and resource-limited IoT and edge devices.
• Define success metrics, work breakdowns and roadmaps, produce executive reporting, and run operating reviews (MBRs, ZBB) and risk reviews.
• Oversee the data lifecycle, including dataset acquisition, annotation pipelines, model evaluation and third-party vendors.
• Raise AI literacy across customer-facing product areas, and coach and mentor junior TPMs.

Requirements

• Bachelor's degree in computer science, engineering, mathematics, physics or a closely related technical field.
• 7+ years as a TPM, technical lead, or product or engineering manager in software organizations building large distributed systems.
• 5+ years managing complex machine learning programs from concept to production.
• Proven hands-on work with ML platforms and deploying models on AWS, Microsoft Azure or Google Cloud Platform.
• A track record of writing clear technical specifications and architecture documents for multi-tier systems.
• Proven ability to turn vague product requirements into structured plans while balancing competing priorities in a fast-moving setting.
• Preferred: Master's or PhD in computer science, artificial intelligence, electrical engineering or a related quantitative field.
• Preferred: Background as a former ML researcher, engineer or engineering manager, and the ability to write Python to evaluate, benchmark or triage model performance.
• Preferred: Direct experience deploying ML or computer vision models on-device under tight power, compute, memory and latency limits.
• Preferred: Fluency with deep learning and LLM frameworks, third-party ML platforms, continuous learning loops and AutoML systems.
• Preferred: Deep understanding of AI safety, ethics and model fairness. Public speaking, publications or active contributions to the ML community are a strong plus.

Conditions

Hybrid role based in the Seattle, WA office.

Work onsite Tuesday through Friday, with the option to work remotely on Mondays unless an approved workplace accommodation applies.

Compensation is total compensation: base pay, bonus and stock awards.

Base pay range is $147,675 to $236,280 USD, depending on level, function, training, transferable skills, work experience, business needs, geographic market, or a combination of these.

Benefits may vary depending on the nature of employment and work location.

Some roles may require legal eligibility to work in a firearms environment.

Everyone must follow environmental, health and safety rules and report safety or environmental concerns as they arise.

The company is an equal opportunity employer and hires regardless of race, religion, sex, age, citizenship status, disability, veteran status or any other legally protected characteristic.

Benefits

• Retirement savings plan (401k) with employer match
• Discretionary paid time off
• Parental leave with pay for everyone
• Medical, dental and vision plans
• Fitness programs
• Support for emotional and mental wellness
• Learning and development offerings
• Snacks in the offices