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Open nowPosted 29 days ago

VP Engineering

scaleworks2 open roles

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Your applicationOpen nowVP Engineeringscaleworks

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The clock on this job

Early applications get read.

11.4% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.0%1 day
  2. 4.2%3 days
  3. 11.4%7 days
  4. 17.5%14 days
  5. 34.2%30 days
  6. 43.5%60 days
This job: posted 29 days ago

The posting

Who Are We?

Scaleworks is a software fund that acquires and invests in B2B SaaS companies. We are investors and operators who scale great products into great businesses. We apply a hands-on operational model where we take substantial positions in our investments, focus on markets we can lead in, and bring together teams of experienced B2B SaaS operators to help us get there. It puts businesses in a strong position to succeed, using low to no debt and reinvesting every dollar of profit back into growth.

For one of our portfolio companies, we are looking for:

VP Engineering

RESPONSIBILITIES AND HOW WE MEASURE

Weight

What they own

Measured by

30%

Shipping code in live services

Their own contribution visible in the repo, weekly

30%

Rebuilding how we build. Tooling, agents, standards, quality gates

Throughput per engineer up, QA and severity tickets down. Both, or it does not count

20%

Team size and shape. What we stop doing, who stays, hiring bar

Cost per unit of shipped output

20%

AI inside the product, with the VP of Product

Customer-facing AI features shipped

Does not own: product strategy or the roadmap (VP Product), a greenfield rewrite, a growing org.

90-DAY EXPECTATIONS

  • Day 30 — Shipped in every major service. Can tell us where engineering time actually goes.
  • Day 60 — New development method running on live work, with quality gates in place.
  • Day 90 — Measurable throughput change, plus a 12-month plan for team size and shape.

Must have

  • Has led a small engineering team and carried the outcome. Startup CTO, startup VP Engineering, or ran 5 to 15 engineers with delivery on their name
  • Still writes and ships code today. Not "used to be technical"
  • AI-native development as their actual working method, not a pilot. Agents doing real work, evals, model routing, AI-generated tests
  • Can walk through a substantial project they shipped where a model wrote most of the code under their direction, and explain specifically how they made it trustworthy
  • Strong in Python or Ruby, comfortable picking up the other. React exposure
  • Has delivered with no budget and no spare headcount
  • Clear, defensible views on code review and testing standards in an AI-assisted codebase

Nice to have

  • Has merged or consolidated codebases from an acquisition
  • AWS, Kafka, MongoDB, PostgreSQL
  • Has shipped customer-facing AI features, not just internal tooling
  • Has reduced team size while holding or improving output
  • Has worked with a product leader as a genuine peer
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