AI Product Manager

I am a product-minded builder with 10+ years of experience taking software from a vague problem to a live product in users’ hands. I’ve built and shipped multiple consumer products end to end, deciding what to build and what to cut, defining the wedge, shipping it, and watching what real users actually do. I’m not a manager who has only ever specced features for someone else to build. I’ve lived every part of the product lifecycle, which means I bring engineering fluency, design judgment, and ruthless prioritization to the same role.

My most recent product is Synthri, an AI-powered health app I built and shipped to the App Store (US, UK, Canada) with an Android release on Google Play. The core product bet was that people don’t want a wall of biomarker data. They want one legible signal they can act on. So I anchored the entire experience on a single number: the user’s biological age, estimated from their bloodwork. I made the call to lead with that as the wedge, built the OCR pipeline that extracts lab values from uploaded images, and designed an interactive “what-if” engine so users can see how changing one marker moves their result, turning a static report into a feedback loop. I prioritized the roadmap and navigated multiple App Store review cycles by reframing medical claims into a compliant, citation-backed presentation rather than gutting the feature.

Earlier I built and shipped Megalancer, a freelance marketplace where I made every product decision end to end. I defined the trust model (milestone-based escrow via Stripe Connect and PayPal), scoped a real-time messaging experience, and made the call to ship AI-powered semantic matching to connect freelancers and clients. When I found that international users were being silently locked into US-only payout accounts, I prioritized the fix and the remediation of affected users before scaling, the kind of judgment call that protects users before it becomes a support fire. I also chose the pragmatic architecture (MySQL JSON over a dedicated vector database) appropriate to the product’s actual scale rather than over-building.

Building and shipping a range of consumer apps to both the App Store and Google Play has given me repeated reps at the full cycle: defining a concept, validating it, launching it, and making hard calls about what to pivot, what to cut, and what to double down on. One app came out of a deliberate pivot with a pre-committed kill criterion (clear traction within 30 days or move to the next bet). That discipline, setting success metrics up front and being willing to act on them, is the heart of product management.

What I bring to this role: End-to-end product ownership: defining the problem, prioritizing the roadmap, scoping releases, and shipping to real users repeatedly, as the single point of accountability. Engineering fluency: deep full-stack and mobile background (React/Next.js, TypeScript, Node, React Native, Supabase/Postgres), so I can collaborate credibly with engineers, pressure-test estimates, and understand technical tradeoffs firsthand.

AI-native product thinking: shipped real LLM-powered features in production, including OCR, structured extraction, semantic search, and in-app AI chat, so I understand what these models can and can’t reliably do in a shipped product.

Data-informed prioritization: comfortable defining success metrics, running on conversion and retention signals, and making kill/scale/pivot decisions against them. Velocity: a track record of going from idea to shipped product in weeks, not quarters, while owning the full lifecycle.

Stakeholder navigation: managed external gatekeepers (App Store / Play review, payments compliance) and resolved blockers without derailing the roadmap.

I’m looking for a role where I can own a product, make sharp prioritization calls, and ship things that matter to real users, backed by the rare ability to also speak the language of the engineers building it. I’d welcome the chance to discuss how my experience maps to your team’s needs.

Thank you for your consideration.