REST API Experts in Zurich

• 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

• 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

• Built and explored applied GenAI, RAG, GraphRAG, local LLM, agentic AI and document-intelligence prototypes for structured analysis, evidence extraction, semantic search, technical reasoning and decision-useful reporting
• Developed private local-LLM workflows and AI system patterns focused on privacy, reproducibility, reviewability, low-cost inference and practical user control
• Built reproducible Python/R workflows for data analysis, automation, API-driven tooling, validation logic, technical documentation and AI-assisted software development
• Designed workflows around explicit assumptions, traceable inputs, reviewable outputs and failure-mode awareness rather than black-box “looks good” demonstrations
• Supported RAHN AG in a chemical/regulatory environment with data extraction and processing around WERCS, a regulatory application for chemical product and compliance data
• Explored complex application/database schemas and wrote nested SQL queries to extract information for mixture calculations, component relationships, regulatory rules and reporting logic
• Continued hands-on development in Git/GitHub/GitLab/Bitbucket, Docker/Linux deployment patterns, REST/API workflows, error handling, technical writing and fast AI-assisted prototyping
• Built technical writing and documentation workflows that turn complex systems into clear runbooks, checklists, decision notes and user-facing explanations

• Project management: Implementation of SAP & EBX integration for master and reference data management and led development of AI supported services for data management and privacy-oriented solutions
• Business analysis: Executed in-depth requirement gathering and data analyzes for MDM implementation, supported service integration using REST APIs to enhance service interoperability, led the requirement gathering, analysis, and implementation of agent-based AI services
• Technologies: SAP BP & FICO & MM, Tibco EBX, n8n, custom AI development in Java, Python, RDBMS, cloud

• 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.

• Analysis, consulting, and development of a WordPress application for the digital processing and delivery of the Bauma chronicle archive

• Building a framework for automated website testing
• Testing, regression testing
• Defect management
• Release management, UAT, agile testing
• Feature discussions with business
• Test management

• Participating in a strategic enterprise project to introduce a centralized customer data platform ("Single Source of Truth") to eliminate redundant data storage and accelerate digital services

• Analyzing and documenting business and system requirements for migrating large, heterogeneous data sets (ETL) and for continuous data synchronization between core systems and the new platform

• Close collaboration with business units, data engineers and architects to gather and validate requirements, and to ensure data quality, consistency and regulatory compliance

• Defining the migration strategy, specifying ETL processes and synchronization mechanisms, and documenting technical interfaces

• Developing and executing test cases for migration and synchronization processes, and performing defect analysis to ensure data integrity and system stability

• Technologies: SQL, Microsoft SQL Server, Azure DevOps, Confluence, UML, RESTful Services, Swagger, Postman

• 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.

• Worked in mixed teams with several clients
• Performed requirement engineering, proposal and time estimation
• Developed ACLs, business rules, flows, workflows, catalog items, various scripts, UI actions, policies, scoped applications
• Customized mobile apps: Now Agent and Now Mobile
• Implemented integrations using the Integration Hub
• Coordinated continuously with clients during development
• Performed testing and helped clients with testing
• Deployed to production and applied main version upgrades and patches
• Managed CMDB, domain separation and asset management
• Integrated between instances at different clients
• Developed GlideScript: business rules, scripted REST endpoints, extension points, fix scripts, background scripts

• Acted as project lead in different internal projects, including the development and implementation of innovative solutions based on machine learning, virtual and augmented reality with the aim of providing great user experience
• Drove project planning, execution and reporting, designed risk mitigation and schedule adjustment plans to bring the projects on the green path
• Directed the process optimization and conducted project reviews by being the liaison between engineering teams and executive stakeholders
• Served as agile coach and led the scrum ceremonies such as daily stand-ups, sprint planning, sprint review and sprint retrospective

• Deployed and optimized the inference stack on a multi-node DGX B200 cluster across vLLM and SGLang (serving, throughput and latency tuning).
• Built, with a small team, an internal Python library for LM pretraining covering the full training loop: distributed training with PyTorch FSDP, data pipelines, checkpointing, config and hyperparameter management, and experiment tracking.
• Built and evaluated agent scaffolds on interactive game benchmarks similar to ARC-AGI-3, with metrics for how models plan, explore and adapt across multi-step episodes; classified model errors and fed the findings back into scaffold and evaluation design.
• Researched looped transformer architectures.