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Review capacity and leadershipInvental network

Fractional VP of AI engineering

Rolling coding agents out to five engineers is a tooling decision. Rolling them out to five hundred is an engineering-management one: shared workflows, review standards, test-first habits and training that sticks. A fractional VP of AI engineering sets that direction part-time and works with your leads to make it routine.

02 · experts matched 27 cases across their profiles Contracted through Invental Request a review ↗
Lead match
Code review · Arch. review · Arch. design · Due diligence · Vibe-code rescue · Mentoring

AI-assisted development and JavaScript architecture lead

Best for: teams adopting AI coding agents who want quality to hold · JS/TS scale-ups with growing architecture debt · founders with an AI-built app that needs a senior review · corporate teams training engineers in TDD.

engineering leader and principal-level JavaScript / TypeScript architect · North America View profile →
Lead match · 01 engineering leader and principal-level JavaScript / TypeScript architect
— Also matched for this
CTO-level

Continuous-delivery fractional CTO

Best for: solo founders with a vibe-coded MVP · seed startups without a CTO · scale-ups after a funding round · investors needing a quick technical audit · CTOs who want an outside second opinion.

Code review, Arch. review +4View profile →

From the network

Selected cases from these experts’ profiles.

Test-first workflow for a team adopting AI coding agents

A team started using AI coding agents, shipped faster for a month, and now regressions are rising. The expert sets up a test-first loop (spec, failing unit tests, agent implementation, review gate), shows the team how to write tests that catch hallucinated behaviour, and reviews the first PRs under the new process.

You get

A written workflow, test conventions and coached PRs.

Bookable · Team mentoring · Architecture designTypeScript / JavaScript, unit-testing tooling, LLM coding agents
AI-assisted development and JavaScript architecture lead →

Mentoring developers to work well with AI coding tools

Junior and mid-level developers use AI tools but can't tell good output from bad. The expert runs regular sessions on decomposing tasks, writing specs and tests agents can follow, and reviewing agent output critically.

You get

A practice routine, review checklists, and a few weeks of reviewed PRs to show progress.

Bookable · Team mentoringJavaScript / TypeScript, unit testing, LLM coding agents
AI-assisted development and JavaScript architecture lead →

Test-driven development training for enterprise engineers

An enterprise wanted its engineers to write security-critical code with test-driven development. Our expert trained its engineers in TDD and quality-engineering practices for that kind of code.

Track record · large enterprise · large enterpriseJavaScript, unit-testing tooling
AI-assisted development and JavaScript architecture lead →

What engineering leaders do about AI-written code

Everyone is shipping AI-written code; few know how others keep it safe. One of our experts polled dozens of engineering leaders across North America and Europe. Every respondent had AI-written code in production. Security, code quality and losing understanding of the codebase were the top concerns, and roughly four in ten had already had a security incident. Nearly all reviewed AI code at least as strictly as human code, with human review and security scanners as the main safeguards. The expert applies the same rule in their own teams: engineers use AI but stay accountable for what ships.

Track record · cross-industry (many handling sensitive, compliance-bound data) · all sizescode review process, security scanners, CI pipelines
Continuous-delivery fractional CTO →

Questions buyers ask

What does a fractional VP of AI engineering do?+
Sets how the engineering organization uses AI coding tools: the workflow, the review and testing standards, what gets automated and what stays human-owned, and the training to make it stick. It is part-time leadership alongside your existing engineering managers.
How do you train engineers to work well with AI coding tools?+
Through their real work: pairing on actual tickets, test-first exercises, and reviews of AI-generated pull requests that explain why a suggestion is wrong. Short, practical sessions beat a one-off workshop.
How do you stop AI coding agents from producing hallucinated or broken code?+
Write the tests first and make the agent satisfy them. Unit tests turn "looks right" into a pass or fail check, so invented functions, wrong edge cases and silent regressions show up right away. Add small, well-specified tasks and human review of the architecture, and agent output stays maintainable.

How it works

  1. Tell us what you need — the repo or system, the question, and the deadline.
  2. We match an expert from the network, with a second reviewer where it helps.
  3. Scoped work, contracted through Invental — review per pull request, a fixed-scope audit or architecture review, or ongoing capacity.

— Invental · software studio · Montevideo, UY

Tell us what needs a look.

Describe the system and the question. We match a lead expert from this page, or a better fit from the network, and confirm scope before anything starts.

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