Senior Full Stack Engineer (AI Systems) at Jobflow GmbH
Owning and shipping AI-powered automation systems for recruiters and candidates, improving reliability, productivity, and platform scalability.
Jobflow: AI-Powered Recruitment Automation
At Jobflow, I focus on designing and shipping AI-driven automation systems that streamline recruiter and candidate workflows. My role spans AI feature ownership, infrastructure reliability, and platform scalability.
🧠 AI Systems & Automation
I designed and implemented multiple AI-powered workflows that convert unstructured recruiter communication into structured platform actions:
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Interview Confirmation Detection
Built an AI-based confirmation detection system that automatically identifies when a candidate confirms an interview, triggers backend creation, updates calendars, and sends notifications. -
Task Extraction Engine
Implemented a structured task extraction system that converts recruiter messages into actionable candidate tasks with reminders and status tracking. -
AI Analysis & Data Processing Pipelines
Contributed to autonomous data analysis workflows that enrich candidate and job data using LLM-based processing.
My work includes:
- Prompt engineering
- Dataset creation
- Evaluation frameworks
- Structured output enforcement
- Cost optimization strategies
- Continuous model experimentation
⚙️ Scraping Infrastructure & Data Systems
- Built and maintained job scraping pipelines using Trigger.dev, cron jobs, and distributed workflows.
- Delivered partner integrations including IHK and Kaufland.
- Improved scraper reliability and throughput through system refactors.
- Ensured high-quality data ingestion and database consistency.
🧪 Reliability & Quality Improvements
- Implemented automated smoke tests for CV rendering, eliminating recurring regressions.
- Contributed to performance optimizations across search and caching layers.
- Reduced production instability through structured testing and monitoring.
🧱 Technical Modernization
- Led migration from Yarn to pnpm within a large monorepo.
- Improved dependency management and CI reliability.
- Contributed extensively across frontend and backend layers within a TurboRepo architecture.
📊 Impact
- ~195 merged pull requests.
- Recognized as one of the most active contributors in the repository.
- Became the go-to engineer for AI feature implementation and LLM-based systems.
- Delivered measurable improvements in recruiter productivity and workflow automation.
