Technical Writing Experts in Berlin

• 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.

AI Platform Backend – Senior Developer

Brought in to design and build a backend for an AI platform from scratch, including multi-provider LLM orchestration and real-time infrastructure for AI influencer personas at scale.

Tasks and responsibilities

• Architecture and implementation of a multi-LLM orchestration layer with Semantic Kernel to integrate GPT-4 and other providers for core platform logic and AI influencer personas, reducing model-switching overhead by abstracting provider APIs behind a single interface.
• Design and development of a backend from scratch in C# / .NET 10, including domain modeling with DDD, a versioned RESTful API layer, and cloud infrastructure setup on Azure.
• Built a real-time chat infrastructure with Server-Sent Events (SSE), message persistence, and delivery guarantees for live operation of AI influencer personas at scale.
• Developed a media management service with integration of cloud object storage for upload and retrieval of influencer-generated content.
• Created an integration and unit test suite with data seeding for reliable regression testing across all core platform flows, significantly reducing production error rates.

Tools and technologies: C#, .NET, ASP.NET Core, Python, TypeScript, MySQL, Semantic Kernel, EF Core, Minimal APIs, LLM Orchestration, Prompt Engineering, Agentic AI, Generative AI, AI-Assisted Engineering, Claude Code, GitHub Copilot, Google Gemini, OpenAI API, Ollama, Redis, Azure, Azure Container Apps, Azure Database for MySQL, Docker, GitHub Actions, Clean Architecture, Vertical Slice Architecture, CQRS, Domain-Driven Design, REST API, xUnit, Integration Testing, Unit Testing, Jira, Confluence, Scrum

• 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

Specialize in turning complex data from diverse environments into actionable business value through compelling visual storytelling. I am an expert in generating actionable insights and presenting recommendations to business stakeholders. My technical proficiency in SQL, Python, and leading data visualization tools like Tableau and Power BI allows me to deliver a new generation of self-service tools and analytics services.

• Data Visualization & Storytelling: Created impactful data visualizations and dashboards in Tableau and Power BI, effectively communicating findings and presenting actionable recommendations to C-suite stakeholders and business leaders.
• Stakeholder Management: Built effective working relationships with key business stakeholders, data engineers, and other partners to achieve common data-driven goals and targets.
• Insights & Recommendations: Generated actionable insights from complex data analysis for funnel conversion, marketing performance, and ROI, directly influencing business performance and strategy.
• Data Collaboration & Empowerment: Worked closely with cross-functional teams to support the ongoing data needs of internal partners, helping to optimize internal data processes and workflows.
• BI & Data Expertise: Applied extensive experience in data modeling, data collection, data mining, and analysis to deliver end-to-end analytical solutions from stakeholder discovery to production.

Tasks: Design and operation of end-to-end cloud data platforms for enterprise clients in publishing and finance, including infrastructure automation, pipeline development, monitoring, and data quality.

Activities:

• Built multi-layer data architectures on Databricks (Apache Spark, Delta Lake), BigQuery, and GCP
• Fully automated cloud infrastructure with Terraform across 3 environments (DEV/STG/PRD)
• Developed automated data pipelines with Python, dbt, and GCP services for different data sources
• Built monitoring and alerting systems for real-time platform monitoring
• Implemented data versioning and quality checks at every layer
• Designed automated test and deployment pipelines in GitLab and Bitbucket

Achievements:

• 2× production data processing capacity, reduced spike response time from minutes to ≤15 s, server errors ≈ 0
• Replaced 3,000 lines of manual configuration with a reusable automation module for 7 customer domains, configuration errors to 0
• Delivered a complete end-to-end data platform at ~€10/month infrastructure cost
• Migrated 7 database tables with 0 downstream issues
• Removed 100% exposed credentials, eliminated external vendor dependency
• Delivered integration of 3 teams in 1 sprint

• Codebase Evaluation & Problem Design: Designed and stress-tested complex software engineering problems against large open-source Python codebases (including pandas), requiring deep context acquisition and architectural understanding to produce well-scoped, realistic problem statements aligned to strict correctness guidelines.
• Agent Failure Analysis: Assessed LLM coding agent solutions for correctness and completeness, identifying meaningful failures across edge case handling, dtype behaviour, and multi-column NaN propagation logic; documented findings with precision for downstream evaluation use.
• Programmatic Test Suite Development: Authored comprehensive pytest suites to programmatically verify agent-generated solutions against defined requirements, with deliberate coverage of boundary conditions and failure modes not caught by naive implementations.
• Containerised Environment Engineering: Built and debugged Docker environments for reproducible agent execution, including git-based repository provisioning, dependency pinning with npm ci, and multi-stage Dockerfile authoring across Linux-based containers.

• IT training in theory and practice for IT specialists in application development and system integration

• Lead supplier development initiatives and strategic sourcing activities for critical manufacturing components
• Supplier Relationship Management
• Manage supplier qualification processes and establish long-term partnership agreements
• Drive procurement strategy alignment with business objectives and manufacturing requirements
• Supply Chain Optimization
• Oversee supplier performance evaluation and continuous improvement programs
• Cross-functional Team Leadership
• Coordinate cross-functional teams across R&D, procurement, and manufacturing divisions
• Quality Assurance & NPI
• Develop and implement supplier development roadmaps for NPI projects
• Cost Reduction Initiatives
• Establish procurement KPIs and supplier scorecard systems
• Risk Assessment & Mitigation
• Process Improvement

• Designed and implemented scalable ETL/ELT pipelines using Python, SQL, dbt, AWS and Informatica to ingest data from sources such as APIs, relational databases, and flat files into Snowflake, reducing pipeline runtime by ~30%.
• Migrated high-volume datasets from on-premises Teradata to Snowflake using AWS services (S3, Glue, Step Functions, IAM), ensuring data consistency and integrity.
• Applied Kimball methodology to design star and snowflake schemas, improving query performance and reducing Snowflake compute costs.
• Implemented automated data quality checks using SQL-based dbt tests and the Great Expectations framework to detect anomalies and enforce data correctness before production loads.
• Orchestrated ETL workflows in Airflow using Python and managed code deployments via Git with CI/CD best practices to increase deployment reliability and maintain pipeline uptime.
• Built interactive Power BI dashboards and curated datasets to enable data-driven decision-making for stakeholders.
• Maintained technical documentation in Confluence for ETL workflows, and led knowledge-sharing sessions for new joiners.

• Part-time 2-3 days/week
• Developments in the SD module and CRM Interaction Center
• Consulting, customizing in SD module
• Adapting Fiori applications in the SD module
• Approval workflow for credit memos: design, concept, implementation, customizing
• Credit memo request: object type BUS 2094
• If the credit memo request value is below a certain threshold -> automatic release and removal of billing block
• If the credit memo request value is above a certain threshold -> automatic determination of the responsible employee
• The employee receives a work item in their integrated inbox or in My Inbox (Fiori) -> the employee can reject, approve, or edit the credit memo request
• UML modeling in technical documentation
• Creating a Z-table for customer sample line items
• Merging COA1 (delivery) + COA2 (CAQ) forms and adding to the spool request as a single PDF
• Correcting workflow title according to NACE, fixing message "ZBMA title is displayed incorrectly in SBWP (Workplace)"
• Receiving PLM documents from an external PLM system, creating an RFC function module, storing PLM documents in the material master as GOS objects
• On releasing a production order, reading PLM documents from MM and saving them in a shared folder for the MES system
• Displaying the number of inspection methods in a popup when creating an order -> VA01/VA02
• Automatic stock reconciliation LVS IDOC INVCON
• Performing AQUA tests
• IDOC archiving for old IDOCs
• NL_PM_drawings and storing print output, informing MES via ZPPORDER IDOC, writing technical documents
• Using SD user exits, BADIs for various requirements
• Extending screens for customer requests via screen exits
• Creating message types for sales orders, purchase orders, and invoices
• Extending CRM Interaction Center Business Partner -> Overview -> Contract with customer-specific requirements
• New Fiori application departure control with data from Z-table and standard equipment tables, displaying a pie chart, calculating "vehicles in operation"
• Extending Interaction Center Business Partner -> Overview -> new tab on Overview Page with list tables for performance feedback, attachments from GOS objects
• Extending Interaction Center Business Partner -> Overview -> new tab on Overview Page with list tables for PM quality notifications, attachments from GOS objects
• Implementing BADIs in CRM
• File storage on SAP server/UNIX server
• Using BOL/GENIL architecture in CRM development
• Project language: German

• Analyzed multi-source datasets using information-theory metrics such as permutation entropy, informational complexity, and decision-support models.
• Developed algorithms and data visualizations in MATLAB and Python.
• Conducted research and co-authored multiple peer-reviewed scientific publications based on the findings.
• Electrical project design and execution
• Digitalization and smart systems integration
• Supplier and contractor coordination
• Risk and quality management
• Strategic decision making
• Financial and ROI perspective
• Analytical and systemic thinking
• Data-driven decision support
• Problem solving and critical thinking
• Cross-functional team leadership
• Influential leadership

• Spearheaded the development of BW Bridge and Datasphere models, integrating S/4HANA, BW/4HANA, and BDC to enable real-time analytics in SAP Analytics Cloud (SAC).
• Designed and implemented Calculation Views using SAP HANA Modeler, aligning with LEONI's requirement for expertise in BW/4HANA modeling and Eclipse.
• Authored comprehensive technical documentation and RICEFW objects, ensuring clarity and alignment with business requirements.
• Conducted training sessions for internal teams on Datasphere and BW Bridge, fostering knowledge transfer and self-sufficiency.

• Supported R&D efforts for MRI device prototypes, including installation and journey mapping, segmentation, and testing of Modix3D's Big Meter model.
• Contributed to product design by creating enclosure prints for beta prototypes.
• Conducted research and provided actionable insights to improve product functionality.
• Streamlined task organization and implemented process improvements to enhance development efficiency.
• Optimized campaigns with A/B testing mindset.

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.