How to apply for Principal Technical Program Manager, Hardware

About Hayden AI

Hayden AI builds computer vision systems for transit and government agencies. Their mobile perception platform handles bus lane and bus stop enforcement, transportation optimization, and street safety. The company operates at the intersection of edge AI hardware and public sector transit, which is a narrow niche with real deployment constraints.

About the role

This principal TPM role owns a portfolio of hardware programs end to end, from executive strategy through roadmap and delivery. The work centers on edge inference hardware on vehicles: thermal limits, compute constraints, sensor integration, and field serviceability. You bridge perception and platform engineering so AI system requirements shape hardware decisions early.

A typical day

A typical day likely involves working with perception and platform engineering leads on hardware tradeoffs, reviewing program status against roadmap milestones, and resolving blockers across teams. Expect time spent on early R&D planning, supplier or manufacturing coordination, and translating executive priorities into concrete plans. Exact routines depend on team structure, so ask about the program portfolio and reporting lines in interviews.

Who Hayden AI is looking for

• Has run hardware programs through full product lifecycle, including early R&D incubation and volume delivery
• Understands edge AI constraints: thermal envelopes, compute budgets, sensor integration, and field serviceability on vehicles
• Has worked in ambiguous conditions with engineering leadership to convert strategy into roadmaps and plans
• Has driven systemic process improvements across a company, not just delivered individual programs

Tips for this application

• Name specific edge AI or on-vehicle hardware programs you delivered, with thermal, compute, or sensor constraints called out.
• Show how you converted an executive goal into a roadmap and then into shipped hardware. Hayden AI asks for this explicitly.
• Reference transit, government, or public sector deployment context if you have it. Field serviceability for agency customers is a real constraint here.
• Quantify program outcomes: schedule adherence, cost, quality, or field failure rates. Principal-level roles are judged on delivery evidence.
• Address how you handle ambiguity. The posting says collaboration happens in highly ambiguous conditions, so give an example of that.

What to cover in your cover letter

Cover letter should cover: (1) a hardware program you delivered end to end, including edge or embedded constraints; (2) how you translated executive strategy into a roadmap and plan; (3) experience partnering with perception or platform engineering teams; (4) any work with transit, government, or field-deployed hardware.

Research before applying

• Read how Hayden AI's mobile perception system is deployed on buses and what hardware it runs on.
• Look up the specific transit agencies or cities using Hayden AI and what enforcement or optimization problems they solve.
• Understand the regulatory and procurement context for government transit contracts, since this affects hardware program timelines.
• Check Hayden AI's engineering blog, patents, or press for details on their perception stack and edge inference approach.

Likely interview topics

Based on the job description, expect questions about:

• Walk through a hardware program you took from early R&D through volume production. What broke and how did you fix it?
• How do you handle thermal and compute constraints when perception requirements push against hardware limits?
• Describe a time you drove a systemic process change across engineering, not just within one program.
• How do you plan field serviceability for hardware deployed on moving vehicles in agency environments?
• Tell us about a program where executive goals and technical reality were misaligned. What did you do?

Common mistakes to avoid

• Applying with only software program management experience and no hardware lifecycle ownership.
• Describing programs in vague terms without naming constraints like thermal, compute, sensor, or field serviceability.
• Treating this as a standard TPM role and skipping evidence of principal-level scope, like portfolio ownership or systemic change.