
QYRAGY GmbH
Hands-on CTO & Chief Product Owner for AI Matching Platform
Hands-on Chief Technology Officer & Chief Product Owner
Relevance
Why this case matters
This framing makes the decision signal explicit: impact, proof, fit, and AI / delivery relevance for hiring or collaboration.
System impact
Built an AI-powered matching platform from 0 to 1 and combined product, technology, and team design inside an early-stage startup.
AI / delivery relevance
Put AI into the product core early instead of treating it as a thin prompt layer on top.
Proof
0→1
platform built
AI matching
k-Means + NLP
PWA + AWS
scalable base
Especially relevant for
- Hiring
- Fractional
- Startup CTO
- AI-native systems craft
Case context
Overview
Smartjobr started as an AI-powered freelancer matching platform that had to move from first product model to real delivery and operations. I connected matching logic, technical architecture, team building, and platform work in an early-stage startup with fast learning loops, product-market fit work, and direct delivery pressure.
The platform uses k-Means algorithm and NLP for matching between freelancers and projects. Next.js/PWA, AWS infrastructure, and automated BI dashboards connected product usage, technical foundation, and data-informed decisions.
Responsibility
Activities
- Hands-on startup CTO & CPO: Product strategy, technical direction, and team building across engineering, design, and marketing
- AI matching platform: k-Means algorithm, NLP, intelligent freelancer-project matching
- Next.js/PWA development: Cross-platform user experience, web and Android app; migrated the native Android app to a React-based PWA while keeping distribution through the existing Play Store listing
- AWS infrastructure: Lambda, S3, RDS, SQS, CloudFront for scalable architecture
- Platform operations: CI/CD, Cypress tests, monitoring, and product-close operation of the matching platform
- Test-first product development: frequently used Cypress as the working browser to specify, run, and debug matching, PWA, and platform behavior directly while building
- BI & automation: Dashboard development, Slack bot, automated KPI reporting
- Product strategy: Customer feedback, user experience, and learning loops
- Security & privacy: Data protection compliance, secure infrastructure monitoring
- Team leadership: Agile development, cross-functional collaboration, technology selection
Operating mode
Methodology
- Agile development: Scrum, Kanban, cross-functional teams
- Product management: Customer feedback, user experience, market validation
- Startup methodology: Rapid iteration, MVP-first, product-market fit
- AI/ML integration: Data-driven matching, algorithm optimization
- DevOps: AWS infrastructure, automated deployments, Cypress as a working and test browser, monitoring, and operations as part of product ownership
Technical context
Technology stack
The tools are not the point by themselves. What matters is which system layers had to work together.
Frontend
5Backend
3Data & AI
2Databases & Storage
3DevOps
4Messaging & Event Streaming
1CI/CD & Delivery Pipelines
2Tools
6Practices
5Mobile
2Next step
If you want to explore similar leverage for hiring, collaboration, or a concrete transformation, this is the right starting point.
Send a short note about the situation you are trying to assess. I reply personally and will be direct about fit.