Twenty-five years at the seam between
the boardroom and the codebase.
I'm Oshri Cohen — an AI-Native Chief Product & Technology Officer who works as a fractional and interim CTO. I come in to solve hard problems fast: building AI-native engineering and product organizations, turning around troubled software, and leading technical due diligence for private-equity deals. Hands-on, from the inside out, until the problem is solved.
Two and a half decades,
measured in outcomes.
Not years on a résumé. Companies served, teams led, products shipped.
A product-minded technologist who translates both ways.
Fluent in the cap table and the Kubernetes manifest, and able to turn each into the other.
I've spent twenty-five years working the seam between the boardroom and the codebase. Most of what I do there is translation: turning business strategy into engineering that ships, then turning engineering reality back into something a board can actually decide on. Lately that work keeps landing on the same request. Companies want to become AI-native, and that's a much bigger job than adding a feature. It means changing how the product gets built and how the organization runs, until AI is just the default way things work instead of a layer stapled on at the end.
Along the way I've shipped more than ten digital products in HealthTech, e-commerce, manufacturing, logistics and finance, usually with my hands on the architecture, the pipeline, the UX and now the AI. Since 2018 I've done it as a fractional and interim CTO, for north of thirty companies, nearly all of them in the US. At the busiest stretch I was directing twelve engineering teams scattered across seven countries. Before the consulting years I sat in the full-time chairs too: VP of Engineering at an intelligent-transportation company, then CTO of a healthcare EMR platform.
The thread through all of it isn't a favorite technology. It's the order I make decisions in. I start from the product and the business and let the architecture, the team and the tooling fall out of that, rather than picking a stack first and hoping the business catches up. I've turned that habit into a method I can repeat, but the method only earns its keep because I build. I write code, I hire, I run the team. I don't hand over a deck and disappear. And the thing I keep coming back to is whether the work actually holds up for the people using it: customers, sure, but also the operators quietly keeping the business on its feet.
I work with companies across the US, remotely, on Eastern Time. My own path ran in the less common direction. I studied business at McGill and learned to code afterward, and that order turned out to be the whole advantage: I can read a cap table and a pull request in the same afternoon and keep both straight.
Also known as: AI-native CTO · fractional CTO · interim CTO · Chief Product & Technology Officer · CPTO · technical co-founder for hire.
I think from the product and the business first, then rebuild how the company operates so AI is the default — an AI-native transformation, not a feature bolted on, in service of business development.
The hard problems I'm brought in to solve.
The shapes differ, but the situation usually rhymes: the technology is either in trouble or in transition, and somebody has to own it.
AI-native transformation
Rebuilding how the product is built and how the org runs so AI is the default. Production AI in the product and the pipeline, an AI-first SDLC, and the AI-native team to carry it — measured against the P&L, not against demos.
AI-Native LeaderFractional & interim CTO
The senior technology seat, part-time or in the gap. Strategy, architecture, hiring and delivery owned end-to-end, sized to what the company actually needs and built to hand off to a permanent leader.
Fractional CTOPE technical due diligence
A credible technical read before a private-equity deal closes, and an AI-native value-creation plan after. Architecture, team, security, spend and AI leverage, assessed against the thesis the investment rests on.
Technical due diligenceTurnarounds & troubled software
Troubled products made predictable. I find the real root cause, not the loudest symptom, then stabilize delivery, rebuild trust with the board, and drive the team toward elite DORA performance.
Turnaround CTOLegacy modernization
Modernizing systems that have outgrown their architecture — and traditional organizations making their first serious software or AI bet, where there's no legacy stack to fight and the operating model can be designed AI-native from the start.
Security & compliance
Security and compliance built into the work, not bolted on after. SOC 2, HIPAA and GDPR posture set up so it survives an audit and a scale-up, with security in every pull request.
Most advisors stop at the deck. I keep going.
The distinction that defines the work: strategy is the easy half. The build is the point.
Hands the company a strategy and leaves
- , Delivers a deck, a workshop and a list of AI use cases, then exits
- , Talks about AI in the abstract; never ships it into production
- , Treats the org chart as someone else's problem to solve later
- , Measures success by the strategy being accepted, not by the outcome
- , Leaves the hard part — building it — to a team that wasn't there for the thinking
Owns the problem and stays until it's solved
- →Sets the direction, then builds it: production AI in the product and pipeline
- →Ships hands-on — architecture, code, security, eval and cost control
- →Designs the architecture and the org chart together, both derived from the P&L
- →Measured on the outcome: margin moved, risk retired, delivery made predictable
- →Hires and runs the AI-native team, then hands off — no permanent dependency
The career behind
the method.
Executive seats, a founding team, and seven years as a fractional CTO. Where the experience comes from.
Chief Product & Technology Officer · EdTech
- Led product, engineering and AI-native transformation for an online learning platform
- Owned the full product and technology org from strategy through delivery
Consulting & Fractional CTO · USA · Remote
- Strategic technology partner to 30+ startups and growth-stage companies
- At one point directing 12 engineering teams across 7 countries and 4 time zones
- AI-native transformation, turnarounds, PE due diligence and legacy modernization
VP of Software Development · Intelligent Transportation
- Restructured into bimodal teams for a +30% gain in delivery efficiency
- Introduced CI/CD that cut deploy times by 40%
Chief Technology Officer · Healthcare EMR Platform
- Modernized the integrated care platform
- Owned health-data compliance across the product
Director, Principal & founding-team roles
- Director of Technology at a hospitality-wellness platform — POS integration across hundreds of restaurant systems
- Principal Engineer on the founding team of a no-code automation startup — task execution engine & workflow orchestration
- Director of Engineering at a 350+ person market-research firm — digital transformation of the research & analytics platform
BA, Business Administration · McGill University
- FounderFuel mentor and Montreal CTO Meetup co-organizer
- Business first, engineering second — the order that ended up shaping how I work
What you can count on.
The engagements change shape. These don't.
Business first, always
Every technical decision starts at the P&L — revenue, margin, risk — and is reasoned down to the stack, never the other way around.
Hands-on, not hand-wavy
I build, ship and hire inside the engagement. The part most advisors skip is the part I'm there for.
AI-native by default
AI is evaluated at every turn as a lever and measured against the business, not adopted because it's the trend.
Measured continuously
DORA for delivery, cost and quality for AI systems. Progress stays legible to the board, not a matter of faith.
Both languages, fluently
I read a cap table and a Kubernetes manifest in the same afternoon, and translate each into the other.
Built to hand off
Every engagement ends in a transition — an internal hire, an advisory cadence, or a trained team. No permanent dependency.
About me, answered.
The things founders, CEOs and investors ask before we start.
Who is Oshri Cohen?
Oshri Cohen is an AI-Native Chief Product & Technology Officer who works as a fractional and interim CTO. He has 25 years in software, 20 of them in technology leadership, and since 2018 has served 30+ companies — almost all US-based — building AI-native engineering and product organizations, turning around troubled software, leading technical due diligence for private-equity deals, and modernizing legacy systems. He works hands-on, from the inside out, and serves companies across the USA remotely on Eastern Time.
What does an AI-Native Chief Product & Technology Officer do?
It's the senior seat that owns both product and technology, run AI-native. Rather than bolting AI on as a feature, Oshri rebuilds how the product is built and how the organization runs so AI is the default: production AI in the product and the pipeline, an AI-first software development lifecycle, and the team and operating model to carry it — all derived down from the business, not from the technology.
What kinds of companies does Oshri work with?
Primarily $10M–$50M software and software-enabled companies past product-market fit, where a technology decision now moves the valuation rather than just the backlog — founders, CEOs and boards, plus private-equity investors who need a technical read before a deal and a value-creation plan after. He also works with traditional organizations making their first serious software or AI bet, where the operating model can be designed AI-native from the start.
Fractional, interim, or full CPTO — what's the difference in how he engages?
Fractional means the senior technology seat part-time, on an ongoing basis. Interim means stepping fully into the gap when a company is between CTOs and needs the role owned now. CPTO means owning product and technology together. In every case the work is sized to what the company actually needs and built to hand off to a permanent leader — never a permanent dependency.
Where is Oshri based, and does he work remotely?
He serves companies across the USA and works remotely on Eastern Time. The practice is remote-first; engagements run distributed, which is also how he has directed as many as 12 engineering teams across 7 countries at once.
What is his background?
A McGill University business graduate (BA, Business Administration, 2006) who learned to code — the wrong-way-round path that lets him translate between the boardroom and the codebase. He has held executive seats as VP of Engineering at an intelligent-transportation company and CTO of a healthcare EMR platform, was on the founding team of a no-code automation startup, and has run engineering at a 350+ person firm. Since 2018 he has worked as a fractional and interim CTO.
How does he actually run an engagement?
Through The Business-Down Method: a repeatable, four-movement approach — Read, Direct, Build, Operate & Optimize — where every technical decision is derived down from the P&L. The discipline is fixed; the solution is built with today's state of the art and bespoke to your numbers every time.
How do I get in touch?
Email hello@oshricohen.me or call (514) 777-3883. The lowest-risk way to start is a focused Read — a diagnosis of system, org, spend and AI leverage that ends in a 90-day plan you keep whether or not we continue.
Have a problem
worth solving?
If the technology and the business are tangled together and someone has to untangle them on purpose, that's the work I'm built for. The fastest way to find out if I can help is a focused Read — yours to keep either way.