Energy Trading Experts in Germany

• Build and operate an end-to-end MLOps platform on Azure ML and Kubernetes (Kubeflow) for the automated deployment, monitoring, and scaling of forecasting models (including Temporal Fusion Transformer, Informer, Autoformer).
• Implement CI/CD pipelines in Azure DevOps for the full ML lifecycle – from resource provisioning (Terraform), data transformation (Hugging Face Datasets, Pandas, PyTorch, CUDA cluster) through training and evaluation to model registry and endpoint deployment.
• Integrate MLflow for experiment tracking, model versioning, performance monitoring, and automated registration in the Azure Model Registry.
• Develop and containerize PyTorch training jobs (Azure Notebook, Jupyter Notebooks) for price and time series forecasting (PFC models) with automatic rollout via Azure ML Endpoints and REST/gRPC interfaces, Docker containerization, secured with OAuth 2.0.
• Set up monitoring and alerting mechanisms (Prometheus, MLflow Metrics), log centralization, and cost monitoring.
• Automate infrastructure provisioning and model deployment using Terraform, Helm, and Azure CLI; connect to existing market data systems and event pipelines.
• Migrate existing workloads and databases (IONOS → Azure, MongoDB) with integration into central MLOps workflows and internal networks.
• Extend the platform with LLM-based tools (LangChain, LangServe) to integrate GPT-based analysis modules into existing Spring Boot services for market anomaly detection and automated reports.
• Analyze and architect a software solution to process large volumes of data efficiently (>3000 messages/sec.) (market data store).
• Spring Boot / Java 21 container development with RabbitMQ for distributing stock market data via MongoDB (Kubernetes) with fast storage of data in Redis RMaps, deduplication, forwarding messages to Read Model queues, and building Read Models for UI display in MongoDB.
• Integration of RESTHeart to create a REST API for MongoDB.
• Build an Angular frontend to simplify data queries and master data maintenance.
• Agentic coding with remote and local LLMs (Claude Sonnet, Ollama Qwen) and MCP servers.
• Develop Python scripts for transforming and cleaning incoming stock market data (Pandas, scikit-learn).

• Analysis and remediation of security vulnerabilities in a risk assessment system for energy trading
• System analysis
• Threat modeling
• Decision-making on vulnerability mitigation strategies
• Implementation of vulnerability detection mechanisms
• Security scans
• DevSecOps practices
• Technical environment: Visual Studio Code, JetBrains Suite, MS Threat Modeling Tool, DevSecOps, Git, AWS, DynamoDB, SQL Server, Endur, Snowflake, Orca
• Languages: C#, JavaScript, TypeScript, Python, PowerShell, Bash, Terraform, SQL

Clients: CARIAD, AUDI AG

• Built and deployed enterprise MLOps pipelines using Azure Machine Learning and Databricks. Reduced model release cycles by 95 percent, from four weeks to two days, through automated CI CD workflows.
• Delivered cloud native DevOps platforms for ADAS programs using Azure data services, Kubernetes, and Terraform based infrastructure provisioning.
• Designed high availability architectures with automated failover. Cut system downtime by 85 percent for mission critical energy trading platforms.
• Developed and integrated AI agents and enterprise chatbots using LangChain, AutoGPT, and GPT models. Enabled autonomous workflows and decision driven automation.
• Reduced cloud infrastructure spend by 40 percent through autoscaling strategies, spot instance usage, and policy driven resource governance across Azure and AWS.
• Partnered with Data Scientists, ML Engineers, Product Managers, and executive stakeholders to deliver large scale automotive and energy solutions.
• Implemented GitOps driven CI CD pipelines supporting automotive software delivery for over 500 engineers across distributed product teams.
• Designed and operated Kubernetes platforms on Azure AKS. Improved deployment stability and reduced rollback events by 70 percent.
• Implemented observability and monitoring stacks using Prometheus, Grafana, and Azure Monitor. Achieved 99.9 percent service availability targets.

Co-founded an AI-native language learning startup, defining the product vision, AI architecture and technical roadmap. Designed and built the AI and backend stack, including LLM fine-tuning pipelines, custom agentic workflows, and scalable inference infrastructure. First product currently in private beta.

Lead Product Designer for BSH's Crosschannel / D2C e-commerce platform — translating complex business requirements into scalable, user-centered shopping experiences for B/S/H/ and partner stores worldwide.

• Design UI, user flows, and components for a multi-themed design system serving 10+ brands — libraries, token structures, and cross-product consistency.
• Drive Design Ops: leaner workflows, cleaner processes, scalable practices.
• Align product, engineering, and business stakeholders on priorities and design decisions for smooth delivery.
• Partner with Business Analysts to frame problem spaces and validate assumptions before pixels.

• Process management, project management
• Business process modeling market-to-order, order-to-cash
• Replacement of an existing CRM system
• Salesforce energy & utilities cloud, Aurea CRM, SAP-Signavio, iGrafx

• Further development and partial new development of a distributed cloud application for providing data in energy trading
• Independent implementation of the infrastructure (IaC)
• Creation of automated CI/CD pipelines, containers, REST APIs, and Lambdas
• Continuous cost and performance optimization
• Collaboration in an international Scrum team and with experts in energy trading
• Technologies: C#/ASP.NET Core; EF Core; PostgreSQL; Terraform/AWS CloudFormation; HTTP; REST/Web API; Swagger/OpenAPI; Azure DevOps; Rider; VS Code; git; Docker; AWS (S3, EC2, Fargate, Lambda, Step Functions, Secrets Manager, VPCs, ALB/NLB, RDS, Cloudwatch, AWS CLI, Amazon MQ); Redis; OAuth; OpenID Connect
• Languages: C#; TypeScript; HCL; Docker; Bash; PowerShell; YML; JSON

• Thorough process analysis to identify weaknesses and assess optimization potential

• Precise modeling of business processes using BPMN 2.0

• Creation of detailed requirements and functional specifications to document use cases

• Comprehensive gathering of existing company processes

• In-depth process analyses to uncover potentials

• Moderation and facilitation of workshops with subject matter experts and executives

• Taking on project management for selecting and implementing a new ETRM system environment

• Working within a Swiss-regulated Virtual Asset Service Provider (VASP) offering institutional-grade crypto-fiat financial solutions
• Contributed to on-/off-ramp infrastructure enabling clients to convert between cryptocurrencies and fiat currencies
• Supported the rollout of Web3 payments & third-party payment services to streamline crypto operations for businesses
• Engaged with AML/KYC / regulatory compliance to ensure operations met Swiss regulatory standards
• Assisted in product development or deployment for crypto-backed real estate / luxury goods transactions
• Collaborated with institutional and high-net-worth clients to tailor crypto / financial services offerings
• Bridged traditional banking and Web3 by reducing frictions in fiat-crypto transactions

• Lead developer of Prof. Valmed, the first LLM-powered medical device (utilising RAG on a medical corpus of 2.5M+ documents) to receive a CE certification.
• Designed and implemented cloud-native MLOps infrastructure for ENBW’s energy trading analytics division, enabling scalable deployment and monitoring of predictive models.
• Architected end-to-end testing and validation frameworks for AI/ML systems, ensuring quality, compliance, and robustness in critical and regulated applications.
• Conducted professional training on AI testing, EU regulatory frameworks, and quality assurance for production AI systems.

• Consulting & strategic advisory in areas related systems engineering, infrastructure development, techno-economic feasibility, sector coupling and regulatory aspects of green hydrogen in India to evaluate integration and decarbonization opportunities.
• Developed data-driven models of renewable distributed energy resources (wind, solar and hydel) to evaluate the cost of green hydrogen production, distribution and application, aiming for commercial viability and affordability.
• Spearheaded the modelling of the Indian electricity grid and simulation of load balancing to estimate the short- and long-term energy market flexibility analysis to support energy trading and risk management for hydrogen assets.
• Leading AI-enabled software development to support decision-making and accelerate the adoption of a hydrogen economy in India.

• Spearheading a forming start-up with a team of 3 people
• Managing project management tasks, innovation, strategy, and implementing deep tech solutions in the finance sector and beyond
• Developed avant-garde processes for outdated systems
• Won a partnership with a large finance firm

• Conducting business analysis for battery energy storage systems and their marketing (BESS)
• End-to-end view of optimization and marketing processes including sales, technical qualification, implementation, optimization, marketing, billing, and cross-functional processes
• Designing and facilitating workshops with business units
• Preparing, aligning, and anchoring requirements
• Transitioning to the solution design phase and mapping requirements to IT solutions

• Management, organization, and team leadership of the EID Energy Information Service editorial team (until 06/2024) with a daily online portal and the weekly print magazine
• Giving talks and moderating industry events
• Strategic development of the product portfolio and modularization of content
• Interview partner as an expert for daily press, radio, and TV stations