Resume
AI Product Manager who still builds.
AI Product Manager with an engineer's hands. I spent 2+ years building fullstack products for millions of users, then moved toward deciding what to build. I finished a Master's in AI at UNSW and now work as an AI Product Manager at Enluma Health.
Full Australian work rights (485 visa). Available now.
01 Experience
Where I've built.
Enluma Health · Australia
AI Product Manager · Visit ↗
- AI Product Manager on Consult+, an AI pre-consultation intake tool for specialist practices. Patients tell their history by voice or text at home; clinicians get a structured summary before the consult.
Pedestal · pedestaltech.dev
Co-founder · Visit ↗
- Building an AI communication coach for high-stakes rooms: record, get feedback on words, voice, and presence, drill one weakness, compare two takes.
- Built the Flutter app for iOS and Android end to end: 14 scenarios, 34 drills, the full practice loop verified on both platforms.
- Supabase backend with six edge functions and RLS on every table; raw video never leaves the phone.
- Coach quality lab with deterministic metrics, DSPy few-shot compilation, and DeepEval rubrics behind a live quality gate.
- Ran user interviews, set positioning, pricing, and the waitlist launch, and pitched Pedestal at the UNSW Peter Farrell Cup 2026.
Rekro · Sydney
Product Manager
- Took a 0→1 product from discovery to a production launch, owning the roadmap end to end.
- Drove discovery into PRDs, Figma flows, and an OKR-aligned roadmap; prioritised the backlog toward the MVP.
- Led a six-person engineering team, ran Agile sprints in Linear, and owned final PR review and prod merges. Cut cycle time ~20%.
- Ran competitor tear-downs and lean experiments (smoke, concierge) to de-risk bets before building.
Startmate Student Founder Bootcamp
Founder Fellow
- Full-scholarship fellow. A two-week sprint from idea and team formation to MVP, customer interviews, and investor-style pitching with 1:1 coaching.
In The Deep Swim School · Sydney
Swim Teacher
- Teach children aged 3 to 10. Keep classes safe and structured. An ongoing lesson in patience, communication, and earning trust.
Rekro · Sydney
Software Engineer Intern
- Built 0→1 site components in Next.js and Convex; partnered with the CTO on the near-term roadmap and developer workflows.
Blue Sky Analytics · India
Full Stack Engineer
- Built React/Gatsby UIs and Node/Sequelize REST APIs for an API-first geospatial climate-data product.
- Used MapLibre and D3 to make satellite datasets usable in client workflows.
Bewakoof.com · India
Senior Software Engineer (SDE1)
- Shipped the listing, product-detail, and homepage journeys used by 50M+ recurring users.
- Led frontend for gift-card redemption; supported a festive spike that lifted revenue 65%.
- Cut JS bundle 20% and raised Lighthouse Performance 15% via code-splitting, memoization, and route-level lazy loading.
- Led Localization (Shopping in Hindi). Won 'Fastest Rookie to Rockstar'.
EdTech / Moodle
Freelance Consultant
- Automated enrolment, credentialing, and reporting with Moodle plugins, themes, and APIs. +30% engagement, -40% grading time.
- Led tech strategy and mentored a team of 5 interns; +25% efficiency with JIRA.
The Inkers · India
AI Intern
- Trained a DenseNet to 79% on CIFAR-10; prototyped behavior cloning for steering-angle prediction; explored Winograd convolutions with skip connections.
02 Education
Foundations.
Master of IT, AI & Data Science
2024 - 2026UNSW · Sydney
Graduated 2026. Seventeen subjects across AI and machine learning, data, computer science, and product, design and delivery.
AI & machine learning
Data
Computer science
Product, design & delivery
B.Tech, Computer Science
M.S. Ramaiah University of Applied Sciences · Bangalore
UX Design + Front-End Developer Nanodegrees
2020Udacity
Certifications + programs
- Reforge · Product Foundations (full feature lifecycle: opportunity, design, development, launch)
- Machine Learning, Andrew Ng (Coursera)
- UNSW Peter Farrell Cup 2026, pitched Pedestal
- UNSW Peter Farrell Cup 2025, Startup Pitch (Semi-Finalist)
- Leadership Foundations (UNSW) + Strategic Thinking (AGSM)
- Swim Australia Teacher · CPR/AED/First Aid
- SSI Rescue Scuba Diver
03 Skills
What I work with.
Product
AI / Engineering
Interpretability / research
Data / Process
04 Product craft
What I learned at Reforge.
Reforge runs the programs that senior product leaders at companies like Meta, Stripe, and HubSpot use to level up. Product Foundations walks the full feature lifecycle, opportunity to launch, the way strong product teams actually run it.
Feature opportunity validation
Score an opportunity on user value, business value, and strategic fit before building. Size the upside with a funnel model and pitch it to leadership.
Feature design
Run focused brainstorming against desirability, feasibility, and viability to land on the right solution, not just the first one.
Feature development
Map stakeholders, set milestones, and manage risk through the sprint with defensive and offensive plays. Know the PM's job at each step.
Feature launch & operation
Coordinate the launch, define how performance is measured, and run post-launch communication so the work actually lands.
05 From the projects
Bullet-ready, if you're skimming.
The four AI products on this site, distilled into CV lines.
AI Product
- Wrote the PRD, metric framework, and experiment plan for each of four AI products.
- Reframed model evaluation as a measured release gate, turning a vibes call into a defensible one.
- Designed evidence-first and trust-by-design AI UX (citations, confidence, approval queues, audit) where the guardrail metric protects the user.
- Scoped MVPs with explicit in/out calls and a credible path from MVP to V2.
AI Engineering
- Built and shipped four hosted AI apps (Next.js + TypeScript, Vercel) across evaluation, RAG, multimodal, and agents, each mock-first so the demos run with zero API keys.
- Built an LLM evaluation harness: deterministic checks plus an LLM judge with per-run cost and latency, surfaced as a ship/hold release gate.
- Built a RAG pipeline (chunk to embed to cluster to retrieve to generate) over user feedback with pgvector and a 2-plus-citation grounding rule.
- Built a human-in-the-loop agent with a manual tool-calling loop, approval gates, and an append-only audit trail.
- Interpretability research (UNSW team project): probed the residual stream of five language models with TransformerLens to detect input corruption the output hid; 0.96+ linear-probe accuracy, confirmed causal with activation patching.