TypeScript Experts in Switzerland

• Led architecture and end-to-end engineering delivery for community-driven SaaS platforms serving 2M+ monthly active users.
• Architected and led the migration of a monolithic Python/FastAPI and PostgreSQL database and LangChain with codebase to an event-driven microservices architecture on AWS EKS, sustaining 10x traffic growth from ~150 RPS to 1,500+ RPS with zero re-architecture cycles.
• Defined and enforced engineering standards across services including API contracts, observability baselines, and deployment topology, reducing production incidents by 55% and MTTR from 2 hours to under 25 minutes within 9 months.
• Redesigned the caching and query layer using multi-tier Redis caching and database indexing/partitioning, cutting p95 API latency from 850ms to 180ms (78% reduction) and database CPU load by 45%.
• Built CI/CD platform on GitHub Actions, Terraform, and Kubernetes (EKS) with blue-green and canary rollouts, increasing deployment frequency from ~2/month to 8-12/day and reducing lead time from 10 days to under 6 hours.
• Implemented contract testing, automated load testing, and observability SLOs using Prometheus, Grafana, and OpenTelemetry, raising platform availability from 99.5% to 99.95% (10x reduction in error budget burn).
• Led and grew a cross-functional team of 8 engineers across backend, frontend, and DevOps, scaling headcount from 4 to 8 with 85% retention; owned hiring, onboarding, performance reviews, and career development.
• Partnered with Product, Design, and Client Success leadership as primary technical decision-maker; translated business goals into technical roadmaps and drove build-vs-buy decisions on authentication, search, and AI tooling.
• Introduced AI-assisted development workflows including automated code review and a RAG-based internal knowledge assistant using Graph (GraphRAG, Neo4J), increasing sprint throughput by 30% across two quarters.
• Owned incident command and production support rotation; established runbooks, postmortem culture, and on-call SLOs, reducing weekend paging incidents by 70%.
• Developed and optimized Algorithms using python libraries like Numpy and Pandas.

• Interface role with the SOC team; improved incident response time by 45% through structured escalation processes and proactive security monitoring.
• Defined technical standards for a multi-tenant enterprise platform (10+ services), resulting in a 30% shorter onboarding time for new clients in the public sector.
• Active knowledge transfer and mentoring of a 6-person team; increased team autonomy and established a sustainable engineering culture.
• Reduced time to market by 50% by optimizing CI/CD pipelines and establishing self-service deployments.
• Stack: GitLab CI/CD, Kubernetes, Nexus, Harbor, ArgoCD, HashiCorp Vault, Grafana, Python, PostgreSQL, Java, Spring Boot, Flyway, Quarkus, JBoss, Loki, Go, Kafka, Kustomize, MongoDB

• Created the MetX Assistant and was its primary driver from concept through production with real users; designed and oversaw telemetry and presented the system in demos.
• Built React, TypeScript and Python features for MetX, a scientific weather visualization platform; integrated internal data APIs and improved caching, request handling and rendering workflows.
• Contributed to company MCP tooling and led AI workshops and internal automation initiatives, including experiments connecting AI agents with Slack, Jira and Git.
• Acted as the team's Observability and DevOps subject matter expert, supporting service reliability, deployment workflows, monitoring and troubleshooting.
• Participated in Security, Observability and AI Communities of Practice.

• Solely responsible for managing procurement operations
• WTO tenders in an open procedure
• Invitation process
• Direct call-offs and mini-tenders from framework contracts
• Simap.ch, SuisseOffer.ch, Confluence, Jira, Microsoft 365 applications

• Intelligent Document Processing Engine with OCR & Computer Vision: Architected the end-to-end AI pipeline at the core of the SQPS GenAI document-processing product, which turns scanned paper and PDF batches into organised, searchable documents, combining image pre-processing, OCR and layout analysis for mixed-quality scans. Technologies: Python, OpenCV, Tesseract / PaddleOCR, PyTorch, FastAPI
• Automatic Document Splitting & Classification: Developed models that detect where one document ends and the next begins inside a single multi-document scan, and classify each one by type (invoices, contracts, letters, reports) to enable fully automated filing. Technologies: Python, PyTorch, scikit-learn, Hugging Face Transformers
• Information Extraction & Intelligent File Naming with LLMs: Implemented an LLM-based GenAI extraction system that reads dates, names and reference numbers from unstructured documents and uses them to generate consistent, rule-based file names, with configurable naming conventions per organisation. Technologies: Python, LangChain, OpenAI, SentenceTransformers, SQL

• Product strategy, architecture, and technical co-direction
• AI workshops, client onboarding and go-to-market activities
• Design and implementation of AI architectures (LLMs, RAG, MCP, agents, voice, automation)
• Hands-on development of prototypes and production-ready AI integrations
• Consulting clients on AI adoption, workflows, and integration into existing infrastructure
• Collaboration with co-founders on strategic direction
• Collaboration in sales and customer acquisition

Tools and Technologies: OpenAI, Anthropic, Azure, Vercel AI SDK, RAG (Retrieval-Augmented Generation), MCP (Model Context Protocol), FastAgent, VAPI, n8n, make.com, LibreChat, PostgreSQL, OpenAPI, Next.js, Vercel, Docker

• Build prototypes, expand AI skills, and practical application in a startup context.
• Transition phase: further training in prompt engineering, APIs, AI, working on independent prototype projects, and collaborating at a friend's startup.
• Technologies: LangChain, REST, Python, Java, JS, TS, Node.

• Greenfield project M-Zollmanager: Development of an internal platform to support users in booking requirement areas on line items in assessment notices.
• Greenfield project M-Deliveryplan: Development of an internal platform for planning and tracking deliveries in the international transport sector.
• Created functions to predict the estimated arrival time of container ships and goods from the port of loading to the port of destination, considering potential events.
• Developed the TrackAndTrace add-on for M-Deliveryplan to track and plan goods and containers.
• Built a generic AI chatbot for Migros app infrastructure, including ChatGPT integration and creating AI workflows with N8N.
• Developed AI assistants to automate repetitive tasks, such as creating release notes or processing Jira tasks based on N8N workflows.
• Further development and maintenance of the M-LFS, M-Vehicleaccess and M-Worklog apps.
• Used C#, Angular 18, DevOps practices, N8N, Kubernetes, Docker, Jira, Confluence and Azure.
• Ongoing project with continuous development of platforms and workflows.

• Business analysis, architecture, and implementation of a telemedicine platform for pet owners.
• Leading the development team as Product Owner and Tech Lead.
• Introducing agile processes, setting up development guidelines and system documentation.
• Planning and implementing features like video calls, live chat, and marketing automation.
• Implementing AI-based features such as automated tagging of information (missing pet reports, marketplace entries, etc.), preparation of social media content, and processing of conversation transcripts.
• Skills: Angular, NGXS, Tailwind, Java, Spring Boot, Kubernetes, Docker, CI/CD, MySQL, LLMs, RAG, MCP, Redis, OpenSearch.
• Industry: Veterinary medicine.

• Implementations of a code refactoring framework able to refactor thousands of repositories leveraging Generative AI
• Use Python (Django, Flask, FastAPI), Java and Typescript in Azure Cloud (Data Lake, VMs, AI) and GitLab infrastructure
• Mentoring and pair programming
• Obtained Azure AI-900 and AI-102 certifications

• Set up a shift-left DevOps E2E system testing architecture
• Set up "DevOps Shift-left" E2E tests for 240+ applications
• Under NDA

• Supported the team in merging two real estate platforms into a unified Vue.js-based solution
• Developed a custom SSR microservice architecture deployed on AWS Lambdas
• Designed and implemented a map drawing feature
• Took ownership of migrating the microservice from Vue 2 to Vue 3
• Built a scalable SSR microservice architecture using AWS Lambda
• Developed and implemented a critical map drawing feature for real estate visualization
• Successfully migrated the microservice from Vue 2 to Vue 3
• Gained deep knowledge of AWS infrastructure, Datadog, Sentry, and Vite
• Technologies: Vue.js, Node.js, Vite, AWS Lambda, Datadog, Sentry, JavaScript

• Designed large-scale systems and APIs serving thousands of concurrent users.
• Refactored a 650k-LOC monolith and led full AWS migration for stable performance.
• Introduced SLO-based observability, improving reliability and recovery flow.
• Optimised cloud and databases, achieving significant cost and latency reduction.
• Delivered LLM, RAG, and document-automation pipelines adopted in production.