Tech Leads in Berlin

• 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.

OpsWorker turns Kubernetes alerts into root-cause analyses, on top of the monitoring a team already runs. I lead the technical side: the agent architecture, the AWS infrastructure it runs on (fully inside EU regions), and the engineering decisions behind it, read-only in the cluster by default, human in the loop for judgment. The stack underneath: Amazon Bedrock and Bedrock AgentCore, agents built with the Strands Agents SDK, the Claude and OpenAI APIs, and the Kubernetes API.

• Full automation of the software development process: ticket analysis → AI coding agents → pull request → automated code review → deployment
• Multi-tenant architecture with 82 database models and real-time WebSocket monitoring
• Integration of 40+ AI tools with Claude & GPT
• Tech stack: React, TypeScript, Express.js, PostgreSQL, Redis, BullMQ
• Platform in productive use with paying customers

• Building a full-stack e-commerce product using AI-assisted development, deliberately returning to hands-on engineering to validate how AI changes software development workflows and team dynamics.
• Exploring VP Technology, Head of Engineering, and Director of Engineering opportunities where hands-on AI experience meets organisational scaling expertise.
• Open to advisory conversations on AI-augmented engineering teams, technology strategy, platform architecture, and organizational design.
• No registered business. No commercial activity.

• Bootstrapping a CloudOps team and building a multi-cloud provider backend for a low-code Internal Developer Platform (IDP) with env zero

• Introducing user story mapping, ADRs, milestones, and backlog management

• Designing and developing core APIs, setting up CI/CD pipelines, OpenTofu/Terraform scripts

• Representing and communicating the team with third-party stakeholders (e.g. env zero)

• (Cross-)team coaching on DevOps, software design, Terraform, Golang, and agile practices

• Optimized the data architecture (medallion) to better decouple processing stages and improve transparency and reproducibility
• Ensured technical quality of data processing in Databricks by introducing schema enforcement, data quality checks and a structured data architecture
• Orchestrated pipelines with Azure Data Factory
• Professionalized and automated the development and deployment process by integrating Git and GitHub Actions
• Led the Data Engineering team (3 members) in a functional role
• Conducted workshops to optimize and stabilize the data platform and the development process
• Collected and prioritized new requests, maintained the product backlog
• Technologies: Microsoft Azure (Data Lake, Data Factory), Databricks, Apache Spark (PySpark), Python, SQL, Git, Confluence, Power BI, Power Apps, Dataverse, MS SharePoint, Mural

• Shipped Memorable, a production iOS app using on-device CLIP-based semantic photo search. Owned the full stack: Core ML conversion, local inference pipeline, App Store release, and post-launch iteration.
• Built a practical AI deployment framework that covers workflow redesign, use-case prioritization, system integration, eval planning, and human-in-the-loop controls.
• Conducting AI use-case discovery and advisory conversations with professionals in legal, tax, and real estate sectors.

• Led a team of four developers in a comprehensive rewrite of the Heinemann iOS app, successfully navigating a highly undocumented software environment.
• Implemented a frontend-first approach by adopting the backend-for-frontend (BFF) pattern, enabling frontend developers to lead API specification development for enhanced alignment and efficiency.

• 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

I worked on automating cold outreach.

• Developed a queue architecture to support the parallel execution of large volumes of background tasks.
• Integrated multiple email delivery providers.
• Implemented an LLM-based data enrichment process.

Technologies: TypeScript, React, Node.js, Next.js, Drizzle ORM, PostgreSQL, Next-Auth, JWT, Docker, Kubernetes, AWS, CloudFlare, Traefik, Groq, Jest, Figma

• Worked on a customer project under NDA
• Tech stack used:
• Backend: TypeScript, Node.js, NestJS, Express, PostgreSQL, OpenAI API, Docker
• Frontend: TypeScript, Vue.js 3 with Composition API, Vuetify 3, Angular, Angular Material, SCSS, TailwindCSS

• Developing GitHub Actions/pipelines for automatic application deployment
• Supporting the provisioning of Helm charts for the CI/CD infrastructure
• Rebuilding and migrating a Kubernetes cluster using Rancher
• Creating IaC with Terraform for Kubernetes and additional services (monitoring, databases)
• Deploying a highly available Percona Galera cluster (MySQL)
• Implementing a centralized monitoring and logging infrastructure

Led backend engineering across core domains (main backend, notifications, medical knowledge base, results processing), owning delivery quality, team growth, and engineering standards.

Signature Outcomes

Shipped a flexible, no-code membership platform (pricing, packages, duration), enabling commercial changes without engineering involvement and keeping membership tiers coherent over time.

Built a high-impact backend team through mentorship, coaching engineers into independent contributors and establishing onboarding documentation that enabled fast ramp-up.

Scaled the team from 2 → 5 engineers while maintaining delivery cadence and code quality; owned hiring pipelines and onboarding.

Partnered closely with Product during design to assess feasibility, sequence work, and make pragmatic trade-offs between speed, tech debt, and long-term maintainability.

Institutionalized testing and simplicity as defaults, enforcing high test coverage and a “simple-first” architecture approach.

Tech & Practices

Stack: Node.js (TypeScript), Express, PostgreSQL; microservices (Node & Go); event-driven async jobs.

Practices: Testing as a release gate, lightweight design reviews, iterative delivery, documentation-driven onboarding.

Compliance & Security: Led implementation of Privacy Officer recommendations (GDPR and German healthcare regulations).

Geeks Ltd is a UK-based technology company; WordUp is its AI-driven language-learning product focused on personalized vocabulary learning and intelligent educational experiences.

• Coordinate AI product delivery across Product, Engineering, Data, Operations, and leadership, translating user needs into scoped initiatives, sequencing work, surfacing blockers, facilitating hand-offs, and communicating progress.
• Own search, recommendation, retrieval, and content-enrichment features end to end, from requirements and architecture through Python/FastAPI implementation, testing, deployment, monitoring, and rapid iteration.
• Developed low-latency retrieval, ranking, and personalization services using AWS, OpenSearch, DynamoDB, embeddings, and reusable APIs, achieving <1s latency, 22% higher engagement, and 12% higher premium conversion.
• Use AI coding assistants for codebase analysis, scaffolding, refactoring, tests, debugging, and documentation while reviewing every output for correctness, architectural fit, security, maintainability, and user value.
• Represent technical work in planning and stakeholder discussions, gather requirements first-hand, challenge priorities constructively, explain delivery trade-offs, and help teammates make outcome-focused decisions.