Rust Experts in Germany

Built an international e-commerce platform for a multi-vendor marketplace for digital assets from scratch. Designed and operated cloud native architectures at enterprise scale.

• Designed and operated a highly scalable microservice and serverless architecture
• Built the complete cloud infrastructure with Terraform + AWS CDK in AWS
• Provisioned ECS/EKS clusters (Fargate), Application Load Balancers (reverse proxy), and Lambda functions
• Observability & tracing with CloudWatch, DataDog, Prometheus, and Grafana
• End-to-end setup with DataDog (formerly AWS CloudWatch), Prometheus, and custom Grafana dashboards
• Integration of advanced metrics (including ORM mapper) and distributed tracing with Jaeger
• Robust backup and disaster recovery strategies
• RDS Postgres backups and hourly snapshots
• Read-only, asynchronously synchronized replicas with automated master failover in emergencies
• Minute-level rollback capability through versioned Docker images on ECS and Git-based CI/CD pipelines
• Created CI/CD pipelines with GitHub Actions for automated multi-stage deployments (Dev, Testing, Prod)
• Integrated Stripe for international payment processing
• Built a marketplace payment system with multiple parties and payout routines
• Used Algolia for high-performance real-time search of digital assets on the platform
• Federation of services with GraphQL and Hasura
• Later migration to GraphQL Mesh
• Test Driven Development (TDD) - unit, integration, and E2E testing with Jest, Vitest, and Playwright
• Used Next.js / React for modern frontend applications in the nx monorepo
• Enterprise security architecture & access control
• Integration of JWT tokens with Auth0, OAuth, OIDC, IP guards, BOLA protection, and secret vaults
• Authorization concepts with RBAC, ABAC, and native Postgres Row-Level Security (RLS)
• Built internal microfrontends with Retool for fast prototyping and operational business processes

Technologies: ABAC, AWS CDK, AWS CloudWatch, AWS ECS, AWS EKS, AWS Fargate, AWS RDS, AWS S3, Algolia, Auth0, DataDog, Docker, GitHub Actions, Grafana, GraphQL, GraphQL Mesh, Hasura, JWT, Jaeger, Java, JavaScript, Jest, Kotlin, Kubernetes, Monorepo, Next.js, OIDC, Playwright, Postgres, Postgres RLS, Prometheus, RBAC, Redis, Retool, Serverless, Stripe, Terraform, TypeScript, Vitest

• Self-hosted table tennis equipment platform.
• Development of a custom “Racket Builder” that uses a co-evolutionary genetic algorithm to identify, evaluate, and recommend the optimal combinations of racket blades and rubbers based on physics heuristics and player data within a search space of over 4 billion combinations.
• Development of a custom fully automated web crawler to capture equipment specifications, integrating an automated pipeline for image normalization as well as data harmonization via DeepSeek.
• Cloudflare Edge Workers written in Rust to perform low-latency data searches and offload computationally intensive simulations from the main server.
• High performance and accessibility standards across a large Nuxt 4 codebase achieving 95–100/100/100 Lighthouse scores.

Independent, part-time open-source engineering focused on build-time tooling for Next.js, React, MDX, and JavaScript/TypeScript compiler pipelines.

• Built next-slug-splitter to optimize content-driven Next.js applications. It analyzes MDX content at build time, resolves component usage, and generates route-specific handlers so pages avoid sharing the full catch-all component bundle.

• Created supporting plugins and utilities for scoped MDX transformations, nested component dependency resolution, compile-time refinement, safe ESTree evaluation, and object-graph diffing.

• Own architecture, API design, implementation, automated testing, npm publishing, documentation, demos, and performance benchmarking.

Building blocks:

• remark-scoped-mdx: Context-aware AST transformations with nested scope isolation, typed component registries, and prop inference.

• recma-component-resolver: Dependency-graph analysis and selective component forwarding across nested MDX includes.

• recma-static-refiner: Build-time prop extraction, schema validation, derivation, and pruning.

• estree-util-to-static-value and object-graph-delta: Safe static evaluation and deterministic, cycle-safe structural diffing.

Tech Stack:

• Frameworks: TypeScript · Next.js · React · MDX

• Compiler tooling: Unified · Remark · Recma · MDAST · ESTree · ts-morph · esbuild

• Competencies: Static analysis · AST traversal and transformation · dependency graphs · code generation · schema validation · route and bundle splitting

• Tooling: Vitest · tsup · npm · performance benchmarking

In this project, I was responsible for the design and implementation of a new, modular, and highly scalable test bench platform for an automotive supplier. My focus was on developing a robust system architecture and programming the associated software, with consistent use of UML modeling throughout. This structured approach made it possible to greatly increase the reusability of individual LabVIEW test modules and to significantly reduce development time for follow-up projects. I also integrated modern automotive standards such as CAN FD, LIN, and safety requirements, which made the solution future-proof.

Technologies: LabVIEW, Visio, UML, CAN FD, LIN, DMM, Safety, image processing, project management, HMI, C#, C++, Python, Rust, CI

• Delivered MVP-focused full-stack architecture for a health-sector client: Vite/React frontend, backend services on Google Cloud Run, and Supabase for database plus IAM/authentication.
• Supported product requirements engineering and prioritized cost-aware workload placement, implementing browser-side/edge computation where feasible before moving logic to backend services.

PLANT-MY-TREE®-per-order

The application enables Shopify merchants to automatically place tree-planting orders for every incoming order. By integrating ecological contributions directly into the purchase process, the manual effort for tracking and billing reforestation initiatives is eliminated. The system increases transparency for end customers through real-time visualizations of the ecological impact directly in the storefront. The architecture is based on a modular monolith with Spring Boot in the backend and an integrated React app inside the Shopify admin area. The solution uses webhooks to capture order data in an event-driven way and integrates the weclapp ERP system for automated monthly invoicing. An app proxy mechanism provides dynamic statistics such as CO2 compensation and planted trees without any performance loss for the merchant shop.

Tasks:

• Design of the modular software architecture based on Spring Modulith to ensure high maintainability
• Development of the event-driven business logic for evaluating Shopify orders via webhooks
• Implementation of automated invoicing by connecting the weclapp REST API
• Building the frontend using React Router and Shopify App Bridge for native integration
• Design of the database model and implementation of the persistence layer with JPA/Hibernate and Prisma
• Integration of internationalization processes for global use in the frontend and email communication
• Automation of deployment processes using Docker and GitLab CI/CD

Project skills: Java 25, Spring Boot, Spring Security, Spring Modulith, Hibernate, JPA, REST API, PostgreSQL, Maven, Liquibase, React, TypeScript, React Router, Vite, Node.js, Prisma, Zod, Docker, Docker Compose, GitLab CI/CD, Shopify CLI, Shopify App Bridge, Polaris, weclapp, i18next, Lombok, Vitest

• Expert-supervised AI systems for scientific reasoning, model evaluation, and research workflows.
• Built the IAS Problem Solver, an orchestrated system for difficult mathematical reasoning; it achieved 84% in one submitted answer set on the Leipzig mathematics benchmark.
• Built a resumable state-machine pipeline for research-grade mathematics benchmark generation: source selection, LLM-agent-based phenomenon discovery, task synthesis, gold-answer and certificate generation and validation, probing, repair, human feedback, and quality gates, targeting tasks that are difficult, natural, verifiable, and cost-effective.
• Current work extends this into budget-aware AI research workflows for real scientific problems with expert review.

Tech stack: Python, OpenAI/OpenRouter-compatible APIs, embeddings, RAG, SQLite.

• 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

• Designed and implemented a hybrid recommendation system (content-based + collaborative filtering)
• Built end-to-end ML pipelines including data processing, feature engineering, model training, and evaluation
• Developed RAG-based LLM systems using LangChain and vector databases for semantic search and knowledge retrieval
• Established MLOps workflows with MLflow for experiment tracking, versioning, and deployment readiness
• Implemented deep learning models (computer vision & classification) using PyTorch and TensorFlow

• Built and operate a hybrid Kubernetes platform across bare metal and cloud to validate multi-GPU workloads, security-zone isolation, and disaster recovery.
• Operate self-hosted AI coding agents in the platform's Git workflow, from issue triage to pull-request review; every change is gated by manifest diffs and policy checks in CI.
• Co-developed a sensor-fusion and GPU edge-inference platform selected by the European Defense Tech Hub from 50 solutions for field testing.

IOG (IOHK), is one of the world's pre-eminent blockchain infrastructure research and engineering companies.

• Converted a lingering R&D project into a cohesive, production-ready testnet; built and scaled the 35-member engineering team (Core, QA, SRE) to achieve this goal.
• Defined strategic direction and aligned technology development with business objectives as a key member of the leadership.
• Optimized software development processes and implemented agile methodologies, enhancing operational efficiency and code security.
• Delivered projects in a fast-paced startup environment through effective project management and resource allocation.

• Identification of requirements (legal, organizational, and technical)
• Design of solution architectures
• Evaluation of concepts and technologies
• Preparation of decision templates
• Architectural Decision Records (ADR)
• Coordination of implementation
• Review of implementations
• Documentation

• Working on the next iteration of tonbo to make it the most flexible in-process analytical database in the market that scales and is operated with strong availability

• Introduced object scope cache to the remote storage layer to avoid I/O churn

• Working on refactoring WAL to support remote storage

• Taking care of the health of the systems as well as designing the operational story and bringing them to production

• Technologies: LSM, WAL, Arrow, Parquet, Rust

• Crypto quant strategy development, automated trade execution, onchain data client (Ethereum / Solana)
• Data and trade architecture development for liquidity provision