PostgreSQL Expert in Zurich

• Migration of databases from ODA to ExaData
• Migration of databases from ExaData to ExaCC/OCI
• Reduced UCC usage by 10%
• Developing automation scripts using Python
• Performance tuning
• Reduced development databases from 6 TB to 3 TB using Exadata columnar compression
• Improved application performance by 30% using the inmemory option
• Improved non-production Exadata performance by 20% to free up CPU resources before ExaCC migration
• Database patching of Oracle 19c
• Basic Ansible scripting for deployments and database cloning
• Developing an accounting model for a shared Oracle platform
• Migrating single-instance databases to Oracle RAC
• Analysis of RAC issues
• Advising development teams on how to migrate to RAC

• 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

• 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.

• 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.

• Mathematical specification and definition, analysis and software development of the skiving cutter tool motion planning within the skiving machine for simultaneous and sequential gear flank processing
• Twist-free topological manufacturing
• Workpiece flank line modifications
• Workpiece flank line and profile corrections
• Workpiece tooth thickness deviations
• Computer vision algorithms for automatic wear detection of the skiving cutter tool
• Software development for corrections of the machine kinematics for the profile grinding product series, including twist-free grinding
• Software development for corrections of the machine kinematics, quality measurement and evaluation for the slot grinding product series
• Performance analysis and continuous improvement of internal design tools (RTDesign)
• Tools used: C#, .NET, TeamCity, git, PostgreSQL, MySQL

• SAP Data Designer ETL, SQL Server, Docker for PharmaSuisse Data Warehouse Application (Application Manager and Developer)
• SAP Business Objects, ABAP on SAP HANA for the Police of the Canton of Bern (Application Manager and Developer)
• Avaloq Connectors to SAP BW for Banque Cantonale de Fribourg

• Contribute to a cross-functional team building a cloud-based bookkeeping platform for SMEs
• Design and implement Java Spring Boot microservices with clear separation of concerns
• Integrate core services via REST and gRPC APIs
• Implement event-driven workflows using RabbitMQ for reliable, decoupled messaging
• Model and manage transactional data in PostgreSQL and leverage Redis for caching

• Took over the analyst and leading developer role in an innovative project helping detection of financial fraud in a major financial institution in Zurich with assistance of artificial intelligence
• Analyzed and implemented new modules, improved performance and user experience, elevated technical documentation and code quality to the standard required by the end client
• Technologies: Java 17, JavaFX, Spring Boot, concurrency, UX, Gradle, Impala