ABOUT
ME

• →Drove consistent MoM revenue growth while expanding the client portfolio across three verticals
• →Built early delivery playbooks that established repeatable execution quality and reduced project rework
• →Managed IoT hardware data pipeline projects alongside standard web/mobile client engagements

Founder origin story — co-founding at ~22 years old, straight out of university. Started as hands-on technical lead and evolved into the client-facing product lead. Origin of delivery playbooks, multi-vertical adaptability, and commercial DNA.

• →Scaled a key in-app surface from near-zero to 100K+ WAUs within 12 weeks through targeted 0→1 feature work and lifecycle orchestration
• →Experiment-led UX improvements delivered +30% completion rates and –50% reduction in time-to-home across onboarding flows
• →Reckitt gamified pilot features drove +34% user engagement and +20% retention; design-system foundations accelerated experiment velocity across markets

Ran two concurrent roles simultaneously — The Parent Inc roadmap AND the Reckitt design contract. Built experimentation culture from scratch at an org that had none. First exposure to white-label B2B delivery and monetisation architecture (paywalls, subscription flows).

• →Contributed to $10M+ in design-partner agreements through delivery alignment, commercial structuring, and stakeholder management with CISO-level enterprise clients (details under NDA)
• →Supported domain-specific ML model training, fine-tuning, and serving at scale using Vertex AI, Hugging Face, and bare-metal infrastructure
• →Increased first-week enterprise activation by implementing guided setup flows and sample alert packs; shaped tiered + usage pricing surfaces and lifecycle retention triggers

Enterprise trust-building in high-stakes, trust-critical environments. Cross-functional deal enablement bridging AI feasibility, compliance (GDPR, AI governance), and commercial promises with CISO-level buyers. Bare-metal ML ops — not just cloud APIs.

• →Reduced pilot latency by 40% through prompt optimisation, retry logic, and service-level tuning on LLM-backed screening workflows
• →Reworked activation & onboarding (checklist onboarding, demo data seeding, role-aware nudges) to measurably reduce time-to-first-value
• →Designed credit-based pricing architecture (Starter / Pro / Business) with volume thresholds, integration tiers, and progressive capability unlocks; established discount governance and unit economics tracking at the token-consumption level

Full-stack ownership — the only role where all three pillars converge. Every design philosophy refined across the previous career stages (eval pipelines, experimentation culture, commercial structuring, enterprise trust) is applied simultaneously here.