Hi, I'm Mereke. I connect engineering depth, clear requirements, and business goals to deliver reliable software.
Career Track Record
Parental Leave & Technical Upskilling — Independent TPO / TPM
Jan 2023 – Present | BerlinCompleted Google x Kaggle AI Agents Intensive ("Vibe Coding"), PSPO I preparation, and built AI prompt frameworks for product discovery.
Technical Product Manager / Technical Product Owner — Goldn
Nov 2021 – Jan 2023 | Heidelberg/BerlinStructured B2B cosmetic marketplace flows. Authored 1-page PRDs with V1 scope boundaries and drove landing page optimizations achieving a +65% user click conversion increase.
Product Management Associate / Consultant — Product People
Nov 2020 – Feb 2021 | Berlin (Remote)Scoped functional MVPs, user stories, and product flowcharts for healthcare (Doctorly) and micro-mobility (Tier Mobility) scale-ups.
IT Project Manager / Technical Delivery Lead — iBEC Systems
Dec 2014 – Aug 2017 | AlmatyLed a 5-person dev team delivering distributor fraud detection software for Samsung Asia-Pacific and directed ERG web redesign (+40% traffic growth).
Selected Work & Case Studies
Demonstrated execution across Fintech competitive intelligence engines, B2B SaaS marketplaces, enterprise anti-fraud platforms, and AI discovery prototypes.
AI-Search Citation Gap
The Hook
Bridging the actionability gap in LLM search: Engineered a Python prototype with a deterministic grounding pipeline to extract competitor Schema.org entities and generate sprint-ready Jira tickets.
Context & Market Problem
Brands monitor AI search visibility across LLM engines (ChatGPT, Perplexity, Claude, Gemini) but struggle to translate rank and citation loss into actionable engineering and content tasks.
What I Did (Architecture & Pipeline)
Engineered a Python/Streamlit prototype featuring dual-reader fetch racing (Jina Reader + AllOrigins fallback) and deterministic grounding. Extracts missing Schema.org and semantic entities with verified dataQuality flags, outputting a 1-click Markdown Brief and sprint-ready Jira ticket (Gherkin AC).
Key Signals & Impact
Demonstrated Computer Science fluency with Pydantic schema validation, rigorous V1 scope boundary enforcement, and an async state architecture for fast analysis.
Competitive Intelligence Neobank Sector
The Hook
A competitor's pricing page changes. The system diffs it, classifies business impact by rule, and ships a sprint-ready Jira ticket — no LLM in the loop, so there's nothing to hallucinate.
Context & Market Problem
European neobanks (Trade Republic, N26, Revolut, Scalable Capital, Bitpanda) deploy frequent pricing and feature updates. Product teams drown in noisy marketing feeds and generic AI tools that guess or hallucinate financial details.
What I Did (Architecture & Specs)
Architected an automated 4-stage deterministic pipeline: HTTP fetch layer with bot-block detection → Zod schema validation → jsdiff line-level diffing → deterministic rule-based classifier. Converts competitor moves into mini-PRDs and sprint-ready Jira tickets (Gherkin AC).
Key Signals & Impact
Demonstrated Computer Science fluency (TypeScript/Zod type-safe data validation), deterministic diff processing (jsdiff line-level comparison), and strict V1 out-of-scope discipline.
Demo runs on static fixture data; live-crawl mode is architected but not the default demo state.
Goldn B2B Marketplace (Cosmetic SaaS)
Context & Problem
- The Conflict: C-level executives urgently needed to capture user persona data during registration to determine product-market fit.
- Engineering Pushback: The engineering team resisted, warning that adding a multi-step survey would severely complicate the core onboarding architecture and introduce user drop-off friction.
What I Did
- Discovery & Benchmarking: Conducted competitor research on onboarding flows and defined strict MVP boundaries in a 1-page PRD to mediate the dispute.
- Architectural Compromise: Replaced the lengthy survey with a frictionless, 2-question micro-modal focused strictly on user role (e.g., formulator, brand owner) and their primary goal.
- Technical Alignment: Partnered with backend engineers to keep the schema lightweight and decoupled from the auth service, ensuring responses logged straight to the analytics pipeline without blocking user activation.
Final Impact
- Established Data Pipeline: Successfully delivered high-signal user segmentation to leadership, enabling them to prioritize roadmap iterations based on actual product-market fit.
- Protected Bandwidth: Avoided a major database schema refactoring and prevented scope creep.
- Maintained Velocity: Kept onboarding completion rates high with minimal drop-off friction, contributing to the platform's broader +65% increase in marketing conversion clicks.
Samsung Asia-Pacific (Distributor Fraud Detection)
Context & Problem
- Revenue leakage and supply chain vulnerabilities occurred due to unmonitored distributor fraud across regional networks.
- Distributors lacked a secure, standardized platform to validate inventory claims and verify serial transactions in real time, resulting in slow manual audits and financial risk.
What I Did
- Led a 5-person international engineering team (frontend, backend, QA) to design, test, and deploy a custom distributor fraud detection application.
- Translated enterprise compliance and anti-fraud business logic into technical system requirements, database verification rules, and automated audit checks.
- Managed sprint planning, backlog grooming, and cross-departmental alignment across remote international stakeholders.
Final Impact
- Successfully launched the custom fraud detection software across regional distributor channels on schedule.
- Automated claim verification, drastically reducing manual auditing cycles and mitigating enterprise financial fraud risks.
Eurasian Resources Group — ERG (Enterprise Web Re-architecture)
Context & Problem
- The legacy digital platform suffered from outdated web architecture, slow page performance, and poor information architecture, causing high bounce rates.
- Technical debt and unstructured content taxonomies prevented visitors and corporate partners from efficiently accessing critical portal resources.
What I Did
- Directed a complete front-end and back-end web architecture redesign to establish modern technical standards and improve site performance.
- Restructured complex corporate data into intuitive user journeys and clear navigation trees.
- Oversaw sprint execution, cross-functional developer timelines, and critical path dependency mapping to ensure a seamless system migration.
Final Impact
- Drove a +40% increase in overall digital platform traffic following the relaunch.
- Delivered a scalable, responsive web ecosystem that eliminated legacy technical debt and improved stakeholder engagement.
📚 Product Bookshelf
Core literature shaping my frameworks for discovery, user interviewing, scope discipline, and developer specifications.
"Inspired" & "Empowered"
Marty Cagan
Product discovery foundations, empowered cross-functional squads, and strategic product vision.
"Continuous Discovery Habits"
Teresa Torres
Opportunity solution trees, continuous customer interviewing, and rapid assumption testing.
"The Mom Test"
Rob Fitzpatrick
Asking effective customer validation questions without introducing bias or false positive feedback.
"Escaping the Build Trap"
Melissa Perri
Outcome-driven product management focused on delivering genuine user value over feature output.
"User Stories Applied"
Mike Cohn
Structuring developer-ready specifications, story points, user role modeling, and acceptance tests.
A Few Questions People Usually Ask
What roles are you currently targeting? ▼
How do you work with engineering teams? ▼
How do you address your recent career gap? ▼
What tools and methodologies do you use daily? ▼
Agile/Scrum: Jira Cloud, Confluence, Miro, PSPO I framework.
Product Discovery: 1-Page PRDs, JTBD, PUVISS feature vetting, Figma.
Technical & AI: Git/GitHub, Postman, Gemini API, Claude/Cursor ("vibe coding"), Python.