Mistral AI Experts in Germany

• Objective/Motivation: PAYONE urgently needs a 360° view of its customers. So far, PAYONE has had no company-wide master data strategy. It is not possible to identify customers across all relevant systems.

The organization is to be enabled to identify customers across all relevant systems. Establishing the basis for master data management at PAYONE

• Challenge: Due to company acquisitions, the system landscape is very heterogeneous. The company is highly dynamic and burdened with many system harmonization and integration projects, meaning that resource bottlenecks and changes in project priorities repeatedly create an almost impossible task.

Due to BaFin findings, the project has a central task and role. The first focus is the migration of all customers, including their AML/KYC data, from the master data backend systems to Salesforce. This is intended to resolve one of the largest findings and establish the corresponding ODD/EDD processes.

In addition, customer data must be harmonized in Salesforce. Previous migrations resulted in duplicate customer records in some cases. The aim is therefore to maintain only one customer in Salesforce and, using the relevant information from the backend systems, also be able to identify which products the customer uses and in which processing systems the customer obtains PAYONE services.

Project: ONE Customer

Budget: €1.5 million

Team: 10/30 employees (full-time/part-time); 4 vendors/providers

Integration: 8 (subsystems/interfaces)

Applications: Salesforce; SAP S4/HANA; in-house developments

Tools: MS Office; Jira, Confluence, SharePoint

Methods: Hands-on; Agile (SAFe); Prince2

• Situation: Increasing demand for privacy-compliant AI solutions for clients in the KRITIS and mid-market sector that need to analyze sensitive media content (audio, video, documents) without sending data to public cloud LLMs.

• Task: Design, deployment, and secure operation of a fully self-hosted AI infrastructure including a custom-built digital management platform for automated media analysis.

• Action: Architected and implemented a multi-tier platform on hardened Proxmox infrastructure with frontend (Nuxt 3, Vue 3, TypeScript, Tailwind 4), backend (Laravel 13, PHP 8.4, Sanctum), data storage (PostgreSQL 16, MongoDB 7), caching/queuing (Redis 7, Laravel Queue), AI workers (Python 3.11, Whisper, DeepFace, Librosa), scheduling (Laravel Scheduler/Cron), and local LLMs (Gemma, DeepSeek, Qwen, Mistral, LLaMA, Phi) via OpenWebUI with segmented network access, API hardening, and audit logging following BSI recommendations.

• Result: Fully GDPR-compliant, on-premises AI platform with zero data leakage to third parties.

• Task: Overall responsibility as an external Head of Cyber Security / CISO-as-a-Service for the design, implementation, and continuous improvement of ISMS according to ISO 27001, BSI IT-Grundschutz, and NIS2.

• Action: Built and managed Cyber Defense Centers (CDC) with SOC operations, integrated SIEM solutions (Splunk, Graylog), established risk-based vulnerability management (Qualys, Nessus, OpenVAS), and conducted regular infrastructure, application, and physical penetration tests.

• Result: Audit-ready ISMS for multiple clients and a 60% reduction in critical vulnerabilities within 90 days.

• Task: Design and execution of NIS2 assessments and operational roll-out plans for KRITIS operators.

• Action: Developed an online assessment tool for automated identification of individual weakness profiles, implemented ISMS optimizations, penetration testing, awareness programs, GRC suite deployment, and delivered C-level presentations.

• Result: Accelerated the consulting process by 50% and successfully prepared multiple clients for NIS2 compliance.

• Task: Incident commander for crisis response, forensics, and business recovery in ransomware attacks and APT campaigns.

• Action: Coordinated with state and federal police (LKA, BKA), performed forensic analysis (OSForensics, Wireshark, Kali Linux), executed disaster recovery and BCM strategies, and developed BTC extortion response strategies.

• Result: 100% recovery rate within defined RTO windows and sustainable post-incident security architectures.

• Action: Planned, built, and operated a hardened multi-VM infrastructure (Proxmox, 15+ VMs) with web and mail servers, Graylog, OPNsense firewalls, CRM/ERP and LLM instances, network segmentation, DDoS mitigation, automated patch management, and backup strategies.

• Result: >99.5% uptime over 20+ years and zero compromises.

• Action: Designed coordinated phishing campaigns with five levels of difficulty, developed e-trainings and webinars in a PDCA cycle, and led red and blue teams.

• Result: Phishing click rate reduced from 35% to under 5% within three campaign cycles.

Development and further development of an internal platform for managing and providing technical resources, virtual machines, and infrastructure services. The platform supports self-service processes and covers functions that are conceptually comparable to cloud management solutions like Azure or AWS.

• Responsible involvement in the design, development, and implementation of new backend and frontend features
• Hands-on development with Java, Spring Boot, Python, and Angular
• Implementation of REST interfaces, business logic, validations, and integrations into existing system landscapes
• Further development of modern web interfaces with Angular, including connection to backend services
• Participation in architecture and design decisions within the team, especially with regard to scalability, maintainability, and clean interfaces
• Containerization and deployment of applications with Docker, Kubernetes, and Helm
• Support with CI/CD processes and deployment to Kubernetes-based environments
• Work in the environment of vSphere, Broadcom, GitLab CI/CD, ArgoCD, Maven, npm, and NuGet
• Close collaboration with developers, business teams, DevOps, and other technical stakeholders
• Analysis of technical requirements, deriving suitable solutions, and independent implementation in an agile team
• Use of GitHub Copilot to support code generation, refactoring, test case creation, and technical documentation

Methods/ tools/ technologies: Languages & frameworks: Java (21), Spring Boot (4.x), Python, Angular, Robot Framework, Kubernetes, Helm Persistence: PostgreSQL, MongoDB, Hibernate, Liquibase Architecture & communication: REST, gRPC, GraphQL, Apache Kafka, OpenAPI, Microservices, Event Driven, Domain Driven Design Cloud & infrastructure: Terraform, Docker, Rancher, Helm, Ansible Security: OAuth2, MS (Entra ID), web security, Keycloak (extensions for detailed group rights) DevOps: GitLab CI/CD, Ansible, Maven, Gradle, Grafana, Prometheus, Git, GitHub Copilot Testing & QM: JUnit, Robot Framework, automated component and integration tests, E2E tests with Playwright, Testcontainers, EasyMock Methodology & approach: Kanban, JIRA, Confluence, Clean Code

• TrendReel, production LLM agent and RAG system (Python, LangChain, OpenAI, Groq/Llama 3, Claude, FastAPI, Kubernetes, PostgreSQL).
• Designed and built a production multi-step LLM agent system: a script generation agent with a per-platform psychology database, 7 viral narrative frameworks, and structured quality scoring, switching between Claude and Groq backends in real time based on output metrics.
• Implemented multi-provider LLM routing (Claude primary, Groq/Llama 3 fallback) with priority-chain failover and quality-based provider switching, achieving 95% inference cost reduction while holding measurable quality thresholds.
• Built an advanced RAG-style retrieval pipeline with per-platform knowledge bases, semantic content matching, and structured output evaluation across 7 decision frameworks, directly analogous to multi-tenant context-based reasoning for enterprise document workflows.
• BrainyAI, adaptive AI learning platform (Python, LangChain, Groq Llama 3.3-70B, OpenAI, Next.js, Supabase, Redis).
• Integrated Groq Llama 3.3-70B with education-level-aware prompting, dynamically adjusting vocabulary depth, citation complexity, and reasoning style across four student proficiency tiers.
• Nexus Prime, multi-tenant SaaS platform for marketing and growth automation (25 modules, 99 backend routers, 153 frontend files).
• Built a 25-module, 99-router multi-tenant SaaS platform covering ad remix, affiliates, WhatsApp inbox, email, and cart recovery, serving four subscription tiers from $199 to $1,999 per month with integrated Stripe, Paystack, and Flutterwave billing.
• AI Video Surveillance Platform, multi-tenant edge and cloud computer vision system currently in active client pitch.
• Designed a multi-tenant AI video surveillance platform combining edge YOLO26 inference on NVIDIA Jetson Orin NX boxes with a central GKE cloud layer (Postgres, Pub/Sub, ClickHouse, R2, Keycloak) for event storage, dashboards, alerting, and multi-tenancy.

• Designed and deployed enterprise Retrieval-Augmented Generation (RAG) applications using LangChain, LangGraph, vector databases, embeddings, and open-source LLMs served through vLLM on GCP GPU infrastructure.
• Built agentic AI workflows using LangGraph with planning, reasoning, tool execution, persistent memory, session management, and Human-in-the-Loop approval mechanisms.
• Developed LLM-powered automation systems integrating BigQuery, SQL pipelines, and external advertising APIs including Meta, TikTok, Amazon, Snapchat, Google, and Pinterest, reducing manual operational workflows.
• Architected multi-agent AI systems for enterprise analytics and decision-support workflows, enabling autonomous task execution and intelligent data interactions.
• Implemented retrieval optimization strategies including multi-retriever architectures, semantic search, context optimization, and query improvement techniques, improving response relevance by approximately 40%.
• Engineered structured prompting strategies, function-calling schemas, and validation workflows to improve reliability of multi-step LLM applications.
• Designed scalable AI services using Python, FastAPI, Cloud Run, Pub/Sub, BigQuery, Docker, and cloud-native deployment architectures.

• Delivered end-to-end product & service design (discovery to delivery) — combining Product discovery, UX/UI Design and Prototyping within an agile delivery framework.
• Applied AI-assisted workflows across research and prototyping to accelerate discovery and validation cycles.

• Provided technical leadership for a 4-engineer team delivering 3 major client platforms in 12 months with microservices architecture and scalability solutions — 100% of scoped majors shipped ahead of schedule vs. planned milestones (baseline: prior releases often slipped 1–2 sprints).
• Ran AI model evaluation and model outputs evaluation on LLM/AI vendor APIs: safety, completeness, instruction adherence, and groundedness review before go-live; cut escaped bad outputs in AI-integrated release checklists from recurring UAT findings to near-zero on final promote.
• Drove API development and performance optimization for payment, exchange, and AI services; fail-closed error handling and payload validation reduced integration rework cycles by ~35% vs. the first AI integration pass.
• Applied software testing, testing frameworks, code quality assurance, and code refactoring with continuous integration gates; first-pass PR acceptance improved across the team and production hotfixes on AI adapters dropped noticeably after review standards landed.
• Owned DevOps practices: Docker, GitHub Actions, Jenkins-compatible pipelines, and version control workflows — cut deployment time ~50% vs. pre-automation baseline and stabilized releases across 3 client environments.
• Implemented verifier/oracle-style pass-fail checks in container sandboxes (Harbor/Terminal-Bench aligned); wrote technical documentation so failures cleared in one review cycle.
• Led cross-functional collaboration with product and client stakeholders; translated AI evaluation scores and risk findings into plain-language briefs for non-technical partners, unblocking go/no-go decisions without extra engineering meetings.
• Used agile methodologies for sprint planning and backlog ownership; mentored engineers so mid-level contributors owned AI adapter modules independently by mid-engagement.

Zerobits is my vehicle for AI-powered automation and custom software development with a clear principle: AI solutions that reach production, not pilot stage. I design and build the systems myself - from first concept and architecture through implementation to deployment and operations.

My focus is on replacing repetitive, manual work with reliable automation and connecting disconnected tools and data sources into one dependable overall system.

Selected work:

• Design and implementation of LLM-based agent systems and RAG pipelines (Anthropic Claude, Mistral, MongoDB Atlas Vector Search + RAG)
• Workflow orchestration for long-running, fault-tolerant business processes using Temporal (temporal.io): saga patterns, event-driven architecture, retry and compensation logic, connecting third-party APIs and internal services into automated end-to-end processes
• Full stack product development: SaaS architecture on Kubernetes, TypeScript/React/NestJS, admin tooling with refine.dev and MUI
• AI-assisted development workflow as standard practice to deliver production software at a fraction of traditional timelines
• Full stack product development: multi-tenant SaaS architecture running on Kubernetes, backend with NestJS/Node.js and Python, frontend with TypeScript, React and Next.js, admin tooling with refine.dev and MUI, CI/CD with GitHub Actions

One of these projects is a product I own and operate - free of any NDA restrictions. I'm happy to demonstrate it end to end.

Enhancement and modernization of a mature Aspire backend application in the environment of a utility company, focusing on new business requirements, testing, legacy code cleanup, and stable backend delivery.

Core contributions & results Implemented new business requirements in the context of customer orders, subcontractors, and cross-company backend processes, and ensured consistent workflows in a distributed system landscape. Modernized existing backend components step by step and reduced technical debt through targeted legacy code cleanup, refactoring, and structured code reviews. Improved the testability of business-critical services by expanding automated tests with xUnit, AutoFixture, and clearer validation structures. Supported the further development of workflow automations and integration processes via microservices, messaging, and API-based communication. Took over source code from external firms, systematically checked code quality, and derived technical improvements for maintainability, stability, and integration. Worked in agile development processes with Jira, Confluence, and Azure DevOps and supported cross-team alignment on architecture, quality, and implementation. Technical metrics Technologies & methods C#, .NET, ASP.NET, ASP.NET Core, Aspire, Docker, RabbitMQ, gRPC, REST API, Swagger, Microservices, NServiceBus, AutoMapper, Autofac, xUnit, AutoFixture, FluentValidation, Entity Framework Core, MediatR, Redis, Consul, Serilog, SonarQube, Azure DevOps, Azure Monitor, GitLab, Google Protocol Buffers, IronPDF, Mailjet, Jira, Confluence, Miro, agile development, Scrum, code reviews, refactoring, legacy code cleanup, workflow automation, power grids

• Conducting cybersecurity readiness checks based on an in-house assessment methodology
• Analyzing the external attack surface using the Graydaxe EASM platform
• Assessing maturity levels and deriving prioritized recommendations for action

• Consulting, design, analysis, software architecture and development
• Designing, developing, and implementing a Pimcore environment and connecting multiple external API systems in a Kubernetes environment, as well as various PIM and ERP systems
• Technologies: Unix environment, design, Symfony development, PHP 8+, software architecture, MySQL/SQL, shell scripting, Git DevOps tasks, AI coding support, Pimcore 12, Shopware 6
• Team size: >10 people

• Quality assurance / management
• Process optimization (laboratory processes, QM/QS processes, etc.)
• Revision and adaptation of existing systems (e.g. document management, equipment management) to ensure compliance with new regulatory requirements
• Implementation/optimization of deviation and/or change control management processes
• GLP and GMP support
• Interim Quality Manager
• QA management
• Audits and inspections
• Conducting internal audits / self-inspections (GLP, GMP)
• Organization, preparation, coordination and support of regulatory inspections including creation of action plans if needed
• Creation and revision of controlled documents (SOPs, qualification documents, manufacturing instructions, checklists, forms, etc.)
• Content review of existing controlled documents for compliance, structure/format and consistency
• "Streamlining" of document management systems
• Basic training (GLP, GMP)
• Refresher training (GLP, GMP)
• Equipment qualifications
• Other topics on request

• Design and lead development of a reactive, highly scalable supervision module
• Created a highly available, distributed solution for real-time visualization of critical system states
• Optimized operational stability and responsiveness
• Technologies: architecture, C#, .NET, Kafka, microservices, AWS, Next.js, React

• Built a JTBD-based prioritization framework for 3,000+ accumulated feature requests, identified 27 broker jobs, validated 8 through 25 user interviews, and used the resulting job map as a live prioritization filter for all incoming channels (Upvoty, CSAT, consulting tickets).
• Responsible for the Scout24 Lighthouse initiative: Document Intelligence with full RAG architecture (semantic chunking, bge-m3 embeddings, pgvector, BM25+Dense hybrid retrieval).
• Reduced lead time of customer feature requests to 3.1 days through code analysis, ticket specification, and independent implementation using a coding agent (Codex).
• Developed an LLM-based support agent (GPT-4o mini, Codex-generated merge requests) that reduced 3rd-level escalations from 40% to 5% of all monthly tickets.
• Integrated six partners through technical coordination, specification, backlog and release management, and led seven full stack developers.
• Eliminated regulatory exposure for brokers in six weeks through risk analysis (BGH ruling on distance selling/GDPR), new audit features, and coordination with legal and data protection officers.