RabbitMQ Experts in Berlin

Transmission system operator – network provisioning platform (team lead)

• Designed the saga orchestrator in Python that provisions network fabrics with rollback.
• Split IP, identity, and resource allocation into bounded contexts with their own databases and typed clients.
• Implemented data access using DDD repositories and units of work, with no SQL in the domain code.
• Required integration tests using real PostgreSQL and RabbitMQ containers, and API fuzzing for every service.
• Introduced an agent workflow where a spec starts each change and a human approves every merge.
• Rolled out OpenTelemetry auto-instrumentation through GitOps across eighteen Kubernetes clusters.
• Led incident response for stuck provisioning and recorded every outage as a post-mortem.

Languages and software used: Python, FastAPI, Pydantic v2, SQLAlchemy async, PostgreSQL, RabbitMQ, Celery, pytest, testcontainers, schemathesis, Helm, Flux CD, GitLab CI, OpenTelemetry, pi coding agent.

Software product company – datacenter simulation SaaS (backend development)

• Built the asynchronous simulation pipeline as the second-largest contributor among more than twenty team members.
• Tagged every image by commit SHA and semver in the GitHub Actions deployment workflows.
• Diagnosed the RabbitMQ memory alarm that froze every simulation and fixed the limits in the Helm chart.
• Converted the test suite to function-style pytest, with coverage reported in every pipeline.

Languages and software used: Python, FastAPI, SQLAlchemy, Alembic, Celery, RabbitMQ, Redis, PostgreSQL, S3, EKS, Helm, Keycloak, GitHub Actions, pytest, mypy, ruff, SonarQube.

Internal AI platform – model serving and telemetry

• Built the FastAPI service that deploys open-weight models on GPU tiers as OpenAI-compatible endpoints.
• Upgraded production EKS by two Kubernetes minor versions and fixed zone-bound storage faults.
• Traced every model call, including its token count, cost, and latency, through the OpenTelemetry operator.

Languages and software used: Python, FastAPI, vLLM, LangGraph, pydantic-ai, OpenAI and Anthropic APIs, EKS, Helm, Flux CD, Terraform, GitLab CI, OpenTelemetry, Grafana.

• ▶ Built real-time voice assistant (STT → LLM → TTS pipeline) benchmarking and evaluating multiple STT providers including faster-whisper and Azure Speech. achieved sub-3s latency, Groq API (Llama 3) with multi-turn memory - directly handling edge cases in dictation, names and passcode recognition.

• 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.

• Creation, maintenance and hardening of Kubernetes clusters employing Ansible and ArgoCD
• Keywords: Ansible, AWX, Kubernetes, NetApp, Prometheus, CI/CD ArgoCD, SSO, Fluent-bit, HAProxy, Calico, Keycloak, oauth2-proxy, SealedSecrets, kubeseal, Aqua kube-bench, CIS-Benchmarks, Aqua Trivy operator

• Developed and deployed microservices in Kotlin and Spring Boot, integrated AWS Secrets Manager to secure credentials and decreased network calls using Spring cache.
• Refactored Kafka consumer using Spring Kafka with semaphore-based backpressure to cap records and keep heap memory stable under spikes; switched to batch upserts to cut down on database invocations; added Testcontainers integration tests for Kafka and database to pave the way for future changes.
• Automated the financial reconciliation workflow in Spring Boot (Kotlin) using Spring Scheduler, transactional boundaries, JPA/Hibernate on MySQL, and Flyway migrations, saving the accounts team 16+ hours per week.
• Designed and dockerized payments end-to-end test framework in Robot (Python) with reusable keyword libraries and profiles; integrated with GitLab CI (JaCoCo XML and HTML reports) to accelerate releases and lift code coverage to 80%.
• Implemented end-to-end observability on Datadog by instrumenting services with Datadog APM, correlating metrics and logs, provisioning dashboards, and creating monitors with burn-rate alerts and anomalies to harden reliability and give stakeholders clear visibility.

• 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.

• Founded an AI-powered scheduling and business-management SaaS for SMBs, owning technology strategy, architecture, product development, UX, billing and go-to-market execution.
• Architected and shipped a multi-tenant platform with REST APIs, RBAC, CRM, billing and notifications, powering the manager dashboard, admin console, booking experience and iOS/Android applications.
• Led and mentored 7 software engineers, 1 DevOps engineer, 1 QA engineer and 1 UX/UI designer, while remaining hands-on across backend, frontend and product delivery.
• Built AI voice and chat agents using Python/FastAPI, OpenAI and Anthropic APIs, RAG, pgvector and tool calling; integrated Twilio, Google Calendar/Meet, Stripe and Firebase.
• Owned production infrastructure and automated delivery across separate environments using Docker, Nginx, GitHub Actions and Grafana; represented the company at accelerators and international startup events.

Selected stack: Python, FastAPI, Node.js, Vue 3, React/Next.js, React Native, PostgreSQL, Redis, Docker

• 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

• Own full-stack development of an AI-native enterprise platform built on TypeScript, React, Vite, tRPC, Hono, and PostgreSQL, delivering AI-powered consulting workflows to B2B clients.
• Designed and shipped a multi-agent AI system using ReAct framework and Claude skills-style workflow patterns, including an intelligent PM assistant with rich system prompts, slash commands, tool integrations, and streaming chat UI.
• Architected an LLM evaluation framework: rubric-based LLM-as-judge, golden datasets, regression testing, and automated quality gating — ensuring consistent AI output quality at scale.
• Integrated LangFuse for end-to-end LLM tracing, conversation replays, and evaluation pipelines, enabling data-driven prompt optimisation that reduced token costs and response variance.
• Built with Drizzle ORM, pgvector, and knowledge graphs for structured data access, semantic search, and relationship-aware AI reasoning across the platform.
• Led TanStack React Query migration across the application — replacing manual state management with centralised caching and automatic refetching, reducing data-fetching boilerplate significantly.
• Practiced AI-native development throughout: Claude Code, Codex, Perplexity SDK, and LLM-assisted testing across the full development lifecycle. Deployed on Vercel + Azure ACA with Biome for linting/formatting.

• Leading engineering organization of 45 engineers across 8 teams while serving dual role as Head of Backend
• Addressed critical organizational challenges including siloed departments, lack of engineering processes, and absence of technical strategy
• Executed comprehensive engineering leadership in people management, organizational design, and strategic planning
• Drove platform modernization including migration to a new Python backend, implementation of React micro-frontends, and transition to event-driven architecture
• Established engineering excellence framework through Architecture Decision Records, RFC processes, and comprehensive technology roadmapping
• Transformed engineering into integrated business partner by building collaboration channels with Product Management and Customer Operations teams
• Reduced escaped bugs by 50% and increased test coverage in legacy systems
• Achieved 100% Q2 roadmap delivery through realistic planning and improved estimation accuracy
• Introduced AI engineering strategy, establishing policies, providing tools, and training team on prompt engineering and agentic workflows
• Saved €10k monthly through infrastructure optimization including AWS IoT to RabbitMQ migration and decommissioning legacy systems
• Improved team engagement from 60% to 100% survey participation and enhanced eNPS scores among team leaders
• Built high-performance team through strategic hiring of Python, Go, and frontend engineers and improved onboarding
• Implementing transition to self-organized cross-functional teams

• Implemented a command line interface (CLI) for integration of REST APIs of various microservices for end users
• Centralized and simplified interaction with services through the CLI
• Implemented a REST microservice for custom data schemas based on an API-first approach
• Developed event-driven control with RabbitMQ to connect to other services
• Deployed services using Docker and Kubernetes and extended the CLI
• Managed complexity and data volume handling through the microservice

• Supported the company's transition from an on-premise architecture to AWS cloud services, modernizing infrastructure and optimizing operational efficiency.
• Leveraged expertise in automation and software implementation to enhance scalability, reliability and profitability.
• Implemented Poetry and Ruff to streamline Python dependency management and code quality checks, improving development efficiency and reducing errors.
• Implemented an automated CI/CD strategy with GitHub Actions, which decreased deployment times and minimized manual intervention.
• Enforced deployment automation for Kubernetes, enhancing the scalability and reliability of applications across the organization.
• Evaluated and implemented Apache Airflow for workflow management, leading to more efficient scheduling and monitoring of data pipelines.
• Created data interfaces for energy traders, enabling them to optimize profit margins through improved data analysis and decision-making tools.

• Project 1: Multi-Tenant SaaS Platform: Data Integration & Pricing Management
• Objective: New development of ELT pipeline (replacement for Java 6 legacy), integration of heterogeneous source systems (CSV, Excel, Email, external DBs), event-sourcing for complete auditability, multi-tenant architecture for tenant-capable data processing
• Challenge: Processing millions of records daily, audit compliance, data isolation between different tenants
• Solution: Stakeholder workshops for requirements analysis, event-driven architecture with Axon Framework and Apache Kafka, AWS services (EC2, S3, Lambda, SQS, API Gateway) for cloud integration, PostgreSQL with tenant-specific schemas for multi-tenant data isolation, REST API design with Spring Boot for external system integrations, comprehensive testing strategy (JUnit, Spring Test, Postman, PACT, ArchUnit)
• Results: ELT performance improved from 30+ min to 1-5 min; 2-3 hours daily saved through workflow automation; 10-20 hours/week saved through event-sourcing auditability; 100% audit compliance; secure multi-tenant data isolation for 10+ tenants
• Project 2: Multi-tenant CRM System Modernization
• Objective: Migration of CRM system (20+ years PHP/MySQL) to Java microservices, Domain-Driven Design implementation, establishment of Test-Driven Development, multi-tenant-capable SaaS architecture for multiple customer tenants
• Challenge: Remodeling complex business logic, no existing test culture, scalable tenant management with data isolation
• Solution: Comprehensive testing strategy (JUnit, Spring Test, Postman, PACT, ArchUnit), multi-tenant architecture with tenant-specific databases, REST API design with Spring Boot for cross-tenant integration, Kubernetes and Docker for container orchestration
• Results: 2× performance improvement; deployment time reduced from 40+ min to 5-7 min; migration without production outages; scalable multi-tenant solution for 15+ customer tenants
• Technologies: Java, Spring Boot 3.x, Angular, Apache Kafka, AWS (EC2, S3, Lambda, SQS, API Gateway), PostgreSQL, Axon Framework, Kubernetes, Docker, GitLab CI, REST API