JSON Experts in Berlin

• Optimized the data architecture (Medallion) to better decouple processing steps and improve transparency and reproducibility

• Ensured the technical quality of data processing in Databricks by introducing schema enforcement, data quality checks, and a structured data architecture

• Pipeline orchestration with Azure Data Factory

• Improved and automated the development and deployment process by integrating Git and GitHub Actions

• Technical leadership of the Data Engineering team (3 employees)

• Led workshops to optimize and stabilize the data platform and development process

• Collected and prioritized new requests and maintained the product backlog

• Technologies: Microsoft Azure (Data Lake, Data Factory), Databricks, Apache Spark (PySpark), Python, SQL, Git, Confluence, Power BI, Power Apps, Dataverse, MS Sharepoint, Mural

• Led development of 15+ microservices (Java 17, Spring Boot) driving customer interactions; migrated from on-prem to GCP Kubernetes, improving scalability and reducing infra cost by 20%.
• Optimized user services with CouchDB caching and API refactoring, cutting response times by 35% and enhancing customer experience.
• Implemented canary deployments, FluxCD GitOps, and CI/CD optimizations in GitLab, reducing release lead time by 25% and enabling zero-downtime rollouts.
• Set up Grafana health checks and Anodot alerts for latency, error, and throughput monitoring, reducing MTTR by 40%.
• Built secure APIs using OAuth2, DPoP, and Gatekeeper, integrated REST and GraphQL, and achieved 90%+ test coverage with unit and E2E tests.
• Mentored junior developers, promoted Agile best practices, and collaborated cross-functionally to deliver high-impact, reliable customer-facing features.

• Designed, built, and launched an internal event planning web application used by over 100 department leads for a large event, despite having no dedicated testing phase.

• Ensured smooth, failure-free operation during first production use, leading to the tool being adopted for future events.

• Automated catering calculations and related workflows, significantly reducing email communication and manual computation effort for meal planning.

• Managed deployment and hosting on a Linux server using Coolify, including application setup and runtime operations.

• Hired and guided a communication designer on UX while independently owning all technical decisions and implementation.

• Self-employed · Berlin, Germany
• Co-founded the company and own the entire technical side: product architecture, backend, frontend, infrastructure and operations.
• Designed and built the Automated Booking System (ABS) as well as the core platform and payment logic.
• Development of AI-powered SaaS products, from architecture through backend and frontend to production operation.
• Technical consulting on product architecture, data protection and permissible automation.
• Building, running and monetising my own API products for AI agents, each available as a REST interface and as an MCP server.
• Full ownership of architecture, infrastructure, billing, legal texts and go-to-market.

• Acted as technical consultant to optimize multi-layer ensemble models combining ResNet, CNN-BiGRU-Attention, and XGBoost.
• Guided implementation of a Logistic Regression meta-learner to solve class imbalance problems, achieving 92.86% accuracy and 0.9644 AUC on PTB-XL and Chapman-Shaoxing datasets.

• Designed and developed AI-powered document processing solutions using Python, OCR, NLP, and Large Language Models (LLMs) to automate extraction, validation, and classification of financial documents, reducing processing time by 75%.
• Built intelligent multi-stage workflow automation pipelines integrating AI services, machine learning models, and enterprise systems to streamline financial operations and improve data quality.
• Developed reusable AI-driven transformation frameworks capable of processing structured and unstructured document formats (XML, CSV, JSON, TXT, DAT) and normalizing them into unified business schemas.
• Designed and developed Python-based REST APIs and backend services supporting enterprise finance applications and high-volume data processing workloads.
• Built scalable data synchronization pipelines between Oracle CFIN and SQL databases, incorporating machine learning models for cash-flow forecasting and AP/AR anomaly detection.
• Architected and deployed Apache Airflow workflows to orchestrate AI-powered data pipelines, automating end-to-end processing from document ingestion through financial system integration.
• Led the migration of critical enterprise integrations from MuleSoft to Python-based services, improving maintainability, performance, and operational flexibility while preserving complete data integrity.
• Managed the full API lifecycle including solution design, implementation, documentation, deployment, monitoring, and production support for mission-critical financial systems.
• Collaborated directly with finance stakeholders to identify business challenges, define solution requirements, and deliver measurable operational improvements through automation and AI-driven workflows.
• Worked closely with cross-functional engineering and business teams to rapidly iterate on features, improve processes, and drive successful adoption of AI-enabled solutions.
• Provided technical leadership through architecture reviews, technology decisions, code reviews, and engineering best practices across integration and automation initiatives.
• Mentored developers, established coding standards, and contributed to improving software quality, maintainability, and delivery effectiveness across projects.
• Provided production support during critical month-end and quarter-close financial processes, performing root-cause analysis and implementing rapid fixes to ensure system reliability and data accuracy.

• Defined and executed product vision & strategy, collaborating with UX, architecture, and engineering teams, resulting in a 30% improvement in user satisfaction across key product touchpoints.
• Owned end-to-end product lifecycle management, overseeing the launch of 5 major product updates, improving product efficiency and feature adoption by 25%.
• Defined and structured epics, features, and user stories; validated and ensured 100% of completed stories met definition of ‘Done' before release.
• Led backlog grooming, prioritization (WSJF, MoSCoW), and sprint planning, ensuring 95% on-time delivery of features in quarterly release cycles.
• Worked with technologies: API, Angular, Node, ReactNative (Mobile), SQL, Kafka, AWS cloud with ES (Elastic search) with JSON file indexes.
• Used Confluence and Jira for maintaining product details and product backlogs for 10 years.
• Used Figma, Sketch, Miro for 4 years.
• Directed cross-functional teams, coordinating with developers, designers, and business units, driving a 40% reduction in time-to-market for critical features.
• Spearheaded product release demos, UAT, and go-to-market (GTM) strategies, leading to a 15% increase in user adoption within the first quarter of launch.
• Optimized member experience on Anthem's digital health platform, resulting in a 20% increase in active user engagement and a 10% boost in member retention.

• Drive migration of enterprise authorization platform from Styra DAS to open-source OPA via Skipper (Zalando's Golang-based ingress proxy) integration
• Optimise k8s resources and integrate native Prometheus metrics with OPA
• Migrate from internal monitoring solution to Prometheus CRs + Dash0

Tech Stack: Java/Kotlin, Golang, Python, Spring Boot, AWS, Kubernetes, Docker, OpenTofu, Prometheus, Grafana

• Owned product delivery for document automation and workflow platform used across multiple legal jurisdictions
• Led integration across 6+ systems using API-based data exchange and structured data mapping
• Partnered with engineering on data models, document generation workflows, and system orchestration
• Evaluated LLM-assisted document automation opportunities to reduce manual drafting
• Built functional prototypes to validate workflow and product concepts
• ~2x increase in case processing throughput
• Enabled multi-state rollout of platform capabilities
• Reduced manual document generation and operational bottlenecks by 80%

• Consulting in the SAP EAM module as part of the migration to EON's S/4 HANA oneERP system

• Review and cost estimation of customer-specific developments (e.g. cockpit for EAM orders, document flow display)

• Preparation of EAM classification data for technical objects (functional locations, equipment) for migration to new classes

• Converts natural language into JQL using RAG and pgvector. Returns structured JSON with a query, chart spec, and plain-text answer. A two-stage router answers general questions without touching the JQL pipeline at all.
• Interchangeable LLM backends: Ollama, vLLM, Groq, Anthropic Claude, AWS Bedrock - switchable at runtime, no code changes. Self-healing JQL: on Jira validation failure, feeds error back to LLM, retries up to 4 times. OCI Vault for secrets. Deployed on Oracle Cloud A1 with GPU inference over Tailscale private network. Open source.

Developed a custom Kotlin Multiplatform app with a Spring backend and AI features.

• Impact: Arcate turns scattered customer signals into ranked product decisions for B2B product teams. Every initiative is prioritized by revenue at risk. Every decision is traceable from customer quote to board slide. Built solo, deployed in production. Model validated at Kendall's tau = 0.924 vs. senior PM judgment across 60 simulation runs.

• Skills: Artificial Intelligence, AI Agent, Large Language Model (LLM), RAG, Model Context Protocol (MCP), Agentic Workflows, Supabase, TypeScript, Deno, PHP, Stripe, PostgreSQL, Product Strategy, Positioning, GTM

• Capabilities:

• Signal Ingestion: Slack, Intercom, Gong, Salesforce, HubSpot. Signals classified by business severity to prioritize revenue-risk decisions.

• Revenue Scoring: Fermi Leverage model. Initiatives ranked by customer ARR at risk, signal strength, and multi-account confirmation.

• Roadmap Intelligence: Every bet traceable from raw customer signal to scored, board-ready decision.

• Built:

• MCP Server (v0.10.0): 12 tools, JSON-RPC 2.0, Supabase Edge Functions, SHA-256 API key authentication.

• Scoring engine: Log-scaled ARR weighting, sqrt-dampened signal strength, multi-account signal confirmation.

• Agentic Workflows: 18 automated pipelines covering release, provisioning, design QA, guard QA, and signal ingestion via Slack agents.

• AI Skills: 7 codified skills including CEO Prioritizer, Design System Enforcer, MCP QA, Simulation Runner.

• Automated QA: Browser-based screenshot validation of every screen against design tokens on every build.

• Full SaaS: Auth, billing, media pipeline, design system. Deployed solo in production.

• Stack: Supabase (Auth, DB, Edge Functions, Realtime), Stripe, Cloudinary, PHP, TypeScript, Deno

The MiDAS program aims to integrate Generative AI across the entire BBM organization. My role is to enable the eBike division to adopt and leverage Generative AI by collaborating closely with the MiDAS team in India.

Management:

• Enable the eBike division to adopt GenAI through tailored solutions.
• Collaborate with the MiDAS team in India to design solutions for Generative AI use cases specific to the eBike division.
• Coordinate with the eBike teams to integrate GenAI systems, tools, plugins, and services provided by the MiDAS team.
• Plan roadmaps with eBike and MiDAS India team Product Managers for the delivery and integration of Generative AI solutions.