Internet of Things Experts in Berlin

• Designing UX for a B2B AI SaaS platform covering the full software development lifecycle, including an orchestration transparency panel showing users which AI model is active at each stage, reducing AI opacity and building user trust in multi-model workflows.

• Architected and deployed private cloud data platform on VMware vSphere, integrating Greenplum MPP, Apache Kafka, Kubernetes, and Apache Solr, and developed real-time ingestion pipelines with Kafka Connect and Schema Registry.
• Led Oracle Exadata to Greenplum migration, rearchitected data models, optimized storage, implemented RabbitMQ with Debezium for CDC, and deployed VectorDB for Generative AI.
• Designed and executed multi-cloud migration PoC across AWS, Azure, and GCP, defined KPIs for throughput, latency, and cost efficiency, executed bulk data transfers, validated analytics and streaming workloads, and delivered full-scale architecture recommendations.
• Assessed legacy on-premises infrastructure and designed modern cloud-native data platforms using Greenplum and containerized microservices, advising on scalability, disaster recovery, and high-availability.

• 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 innovation strategy and the establishment of an AI-native Production System at DIGITALSINN, a content and experience production company.
• Responsibility for innovation direction, AI integration strategy, and production platform architecture
• Establishing a fully AI-driven Production System to transform content operations for brand and agency clients
• Building the strategic positioning of DIGITALSINN as a Production System partner within the DACH market
• Client advisory on AI-native operating models, content automation, and scalable production infrastructure

• Freelance work as a consultant (workshops and coaching for small to midsize companies in the areas of lean startup methodology, digital & AI transformation strategy, agile culture, design thinking)
• AI training & certification
• Project Management

• Led end-to-end discovery and exploratory research to assess user needs, market readiness, and product viability for a workflow management and collaboration proposition
• Identified structural misalignment between concept assumptions and real engineering workflows, preventing premature delivery escalation and investment exposure
• Demonstrated through research evidence that the initial proposition was premature, preventing delivery escalation
• Reframed the value proposition based on evidence and initiated a renewed discovery cycle grounded in observed field practices
• Designed research plans and synthesis frameworks to inform roadmap prioritisation and reduce delivery risk
• Contributed to research operations setup, clarifying team roles and collaboration patterns to support continuous discovery
• Supported alignment between product, delivery, and leadership stakeholders through structured insight communication
• Scale: global platform launched as Think Hub (EU, UK, US, Asia)

Built and scaled a high-performance enterprise API for real-time address validation and data quality with sub-second latency and 99.9 % availability.

Designed and integrated the solution into e-commerce, checkout, and logistics processes of leading European companies. Reduced delivery errors and shipping costs through automated data correction and precise data validation.

End-to-end responsibility for product strategy, technical architecture, software development, enterprise customers, operations, and GDPR-compliant data processing. Combined AI-native engineering workflows, Python, SQL, API integration, data quality, and workflow automation.

• 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

• Impact: Arcate turns scattered customer signals into ranked product decisions for B2B product teams. Every initiative is prioritized by revenue at risk. Every decision is traceable from customer quote to board slide. Built solo, deployed in production. Model validated at Kendall's tau = 0.924 vs. senior PM judgment across 60 simulation runs.

• Skills: Artificial Intelligence, AI Agent, Large Language Model (LLM), RAG, Model Context Protocol (MCP), Agentic Workflows, Supabase, TypeScript, Deno, PHP, Stripe, PostgreSQL, Product Strategy, Positioning, GTM

• Capabilities:

• Signal Ingestion: Slack, Intercom, Gong, Salesforce, HubSpot. Signals classified by business severity to prioritize revenue-risk decisions.

• Revenue Scoring: Fermi Leverage model. Initiatives ranked by customer ARR at risk, signal strength, and multi-account confirmation.

• Roadmap Intelligence: Every bet traceable from raw customer signal to scored, board-ready decision.

• Built:

• MCP Server (v0.10.0): 12 tools, JSON-RPC 2.0, Supabase Edge Functions, SHA-256 API key authentication.

• Scoring engine: Log-scaled ARR weighting, sqrt-dampened signal strength, multi-account signal confirmation.

• Agentic Workflows: 18 automated pipelines covering release, provisioning, design QA, guard QA, and signal ingestion via Slack agents.

• AI Skills: 7 codified skills including CEO Prioritizer, Design System Enforcer, MCP QA, Simulation Runner.

• Automated QA: Browser-based screenshot validation of every screen against design tokens on every build.

• Full SaaS: Auth, billing, media pipeline, design system. Deployed solo in production.

• Stack: Supabase (Auth, DB, Edge Functions, Realtime), Stripe, Cloudinary, PHP, TypeScript, Deno

• RegionRise helps companies to grow internationally by developing expansion strategies, sales operations and organisational readiness for growth.
• Clients include:
• SedaiNow: Interim Chief Strategy Officer, developing the product and go to market strategy
• Elevated Elements Group: Organisational development and commercialisation of a chemical recycling company
• Swiss Green Fuel: Moving the HQ from China to Switzerland, re-branding & positioning, commercial and fundraising strategy
• Prodeval S.A.: Operational sales to enter the German biogas market
• ParallelWorlds.Ai: European expansion for a digital twin platform
• Nomnio: Market entry and growth strategy for a full-stack IoT solution development company
• Mosaic Venture Labs: Supporting the preparation of Taiwanese startups expanding into the USA
• Viessmann Family Office: Evaluating the DACH market for a digital twin & IoT integration solution in the real estate space

Discovery, Delivery, Research, in-depth interviews, user testing, requirements definition, stakeholder management, product strategy, mission & vision, prototyping, sprint planning, prioritization, workshop facilitation, etc.

• Development of a Target Operating Model for integrated hardware, firmware and software delivery.
• Establishment of a PDMO governance model with clear roles, responsibilities and decision rights.
• Improvement of portfolio and delivery transparency for senior management and executive management.
• Integration of a stage-gate product development process with agile software delivery.
• Redesign of release, quality, change and prioritization processes.
• Development of a scalable tooling and reporting architecture for Jira and PPM systems.

• Insurance service provider*

Challenge: Business-critical documents were processed through external OCR providers, with ongoing costs, dependency, and data privacy risks for sensitive insurance data.

Implementation:

• Architecture and production implementation of an on-premise OCR solution with full data ownership
• Methods for recognizing document structures as the basis for automated further processing
• ML-, NLP-, and LLM/VLM-based information extraction, especially from invoices and quotations

Success: Replaced external providers: full data ownership, GDPR-compliant processing, and 75% lower recurring OCR costs per year

Used technologies: Python, Docker, Microservices, FastAPI, PyTorch, Torchvision, MongoDB, MySQL

• Spearheading investor outreach and partnership development as founding MD, building the business case and technical narrative needed to attract initial funding and strategic collaborators in the digital health space
• Designing multi-agent AI systems for autonomous biosignal analysis, orchestrating LLM-based reasoning pipelines with domain-specific medical context to enable intelligent, clinical decision support