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Principal Product Designer

Job in Tulsa, Tulsa County, Oklahoma, 74145, USA
Listing for: Gitwit
Full Time position
Listed on 2026-07-08
Job specializations:
  • IT/Tech
    AI Business & Operations, Product Designer, Product Engineer
Salary/Wage Range or Industry Benchmark: 140000 - 170000 USD Yearly USD 140000.00 170000.00 YEAR
Job Description & How to Apply Below

Compensation: $140,000 - $170,000 / year

Location: Tulsa, OK

Zero-to-One Product Design for AI-Native Ventures

Gitwit is hiring a principal product designer to lead product experiences for new AI products. This is not a role for polishing someone else’s roadmap. You will help decide what the product should be, how the workflow should work, where the user needs to understand or approve what the system does, what should be tested first, and what should ship.

We are looking for a high‑agency product thinker who can turn ambiguous AI venture concepts into testable, usable, shippable product experiences.

What This Seat Actually Looks Like

You come in as a design lead from day one. One or two of the five companies launched each year will be yours to lead through the product lifecycle, from early concept, prototype, first launch, user learning, and iteration. You will work shoulder‑to‑shoulder with discovery, product strategy, engineering, brand, and venture leadership to shape the first version of the company and product.

What

You’ll Do
  • Lead zero-to-one product design for new AI products, from blank canvas through first launch and iteration.
  • Translate user observation, research, and usage signals into product hypotheses, experiments, and design decisions.
  • Design AI workflows where the product may not behave the same way twice – including changing outputs, wrong or uncertain answers, human review, approval moments, fallback paths, and clear next steps.
  • Generate multiple design directions, weigh trade‑offs, make the call, and explain the reasoning clearly.
  • Prototype quickly to help the team learn what is real before overbuilding.
  • Work tightly with product strategists, researchers, engineers, designers, and venture leaders to turn a promising idea into something real enough to test.
  • Create clear, engineer‑ready design systems for early products: flows, components, states, edge cases, interaction patterns, and implementation‑ready specs.
  • Bring discipline and meticulousness to how design gets built across the studio, so engineers are not guessing and each product does not have to reinvent the basics from scratch.
  • Help the studio get smarter with each AI product by capturing what we learn about review, correction, approval, uncertainty, failure states, and user trust – and sharing those learnings clearly with the team so each new venture starts sharper than the last.
What Success Looks Like
  • Stepped into an active venture, understood the product direction quickly, and identified the first design moves that would reduce risk, test key assumptions, and help the team move faster.
  • Took ownership of a new venture concept from the beginning – helping shape the workflow, product direction, prototype, and first version the team can test.
  • Helped run lightweight user tests or experiments with discovery and product strategy to validate core product assumptions.
  • Converted early signal into prioritized design iterations.
  • Created the early design system, flows, states, and specs that engineers need to build quickly and consistently without guessing.
The Kind of Designer We’re Looking For

More than any particular background, we are looking for someone who has done early, ambiguous, zero‑to‑one work and wants more of it. If you see yourself in most of these, we should talk.

  • Zero-to-one ownership. You have taken ambiguous product ideas from early concept to launch, and you can explain the tradeoffs that shaped the product.
  • Product judgment under uncertainty. You can generate multiple directions, pick one, explain why, and define what would prove it wrong.
  • Research-to-product synthesis. You can point to times when interviews, observations, or usage signals changed the product direction – and explain why.
  • AI-native interaction thinking. You are already thinking beyond forms, dashboards, and deterministic flows toward workflows where AI handles work, exposes uncertainty, earns trust, and knows when to ask for human judgment.
  • High-speed craft. You can move from sketch to prototype to implementation-ready detail without getting stuck.
  • Decisive product judgment. You can make a call before everything is certain, explain the reasoning, and keep the work…
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