AI Product Manager
The role asks for
My experience shows
Define the problem and the user before the spec — turn ambiguous market signals into a product thesis.
01
Defined kimkim's market-entry approach for new destinations — which markets to open and why — before building.
Set success metrics up front, then read post-launch signal to decide what ships next.
02
Set metrics and read the signal: removed 60% of manual workflows and grew bookings 3× after shipping integrations and activity scoring.
Make product decisions under ambiguity — scope, sequencing, and stack choice without complete information.
03
Chose the AI stack under ambiguity — model, inference, STT/TTS, and data — through build/buy/partner calls and A/B testing.
Treat governance as product surface — evaluation, guardrails, and sign-off users can trust.
04
Built the evaluation suite as a product with users: defined metrics and methodologies via LLMs4EU that gate go/no-go.
Convert discovery into a prioritized roadmap and OKRs across engineering, data, and commercial.
05
Set strategic roadmaps and OKRs at kimkim, analyzing results to prioritize what to build next.
Own the product end to end, from problem definition to shipped, monitored production.
06
Shipped agentic flows end to end at Blits.ai — payment, catalog search, and tool-use across a multi-LLM stack.
AI Delivery Lead
The role asks for
My experience shows
Take AI products from pilot to production for enterprise clients — scope, milestones, and launch readiness.
01
Led technical delivery of four digital human projects, coordinating engineering and cross-functional partners to production-ready release.
Run delivery across several client accounts and regions at the same time.
02
Leads delivery of conversational AI and digital human products for six Tier-1 banks across MEA, Europe, and Turkey.
Define the quality bar a release has to clear before it goes live.
03
Built and ran the LLM evaluation program end to end — automated, production-conversation, and human re-testing — sustaining a 99%+ pass rate in English and Arabic.
Lead the team that tests and hardens the product before launch.
04
Led the testing team to design experiments, run structured evaluations, and identify the most robust technical solutions.
Surface delivery risk early and give sponsors a clear go/no-go.
05
Delivers vulnerability assessments and LLM risk reports for go/no-go decisions, aligning client executives and compliance around delivery risk.
Take a product from first version to scale — and be able to do it again.
06
Did it three ways: founded Canicula.club and grew its platform to 500+ clients at 50% annual growth over five years; launched kimkim’s product from scratch and scaled it to $4M+ a year across 8 destinations; built and shipped six products of my own, end to end.
Director / Head of AI Product
The role asks for
My experience shows
Set AI product direction across roadmap, architecture, partnerships, governance, and commercial value.
01
Provides forward-looking product strategy on dialect NLP gaps, avatar inference cost, and agentic architecture trade-offs.
Make build/buy/partner calls across the agentic AI stack and vendor ecosystem.
02
Owns build/buy/partner decisions across model selection, inference, data pipelines, STT, and integrations.
Define product evaluation, risk posture, and adoption path for regulated customers.
03
Defines LLM evaluation benchmarks and risk methodologies through LLMs4EU.
Design product surfaces that integrate with regulated enterprise systems.
04
Architects product flows across payment APIs, CRM, core banking systems, and real-time merchant integrations.
Turn client discovery into reusable requirements, patterns, and delivery strategy.
05
Turns banking requirements into scalable partnership frameworks and repeatable AI delivery playbooks.
Own roadmap, OKRs, and commercial outcomes for a product line.
06
Previously owned roadmaps, OKRs, product evolution, content strategy, UX analytics, and commercial growth at kimkim.