Energy Trading Experts in Germany

• Private Equity owned precision grinding machines for Auto, Military & Aerospace – 1200 Employees
• Acting as Interim Group CIO / CISO consolidating Global IT back to Europe – M&A consolidation
• Managed major Security event and post event cleanup – Reporting to regulators
• Performed Vendor & Contract Management – full assessment of capabilities
• Guided Infrastructure refresh & Security Hygiene assessments

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

• Managed the successful overall Trial and Commercial deployment of OpenRAN technology and swap-out of legacy SRAN for 2 mobile network operators in Germany.
• End-to-End Project life cycle governance and coordination of multiple Workstream leads i.e. Operations, Performance, Site Solution Management, Design, SW Delivery, Integration & Implementation, OSS Tools, 3rd-party Resource Support.
• Project planning to cover major milestones by delivering roadmap alignment in compliance with the German Network Regulatory Agency (BNetzA), as a vendor.
• Provided pre/post-Sales support to the Accounts Team for RfP/RfQ submissions.

Independently built a data platform with cross-system process monitoring.

• Designed the Bronze/Silver/Gold architecture and Python-based pipelines for diverse operational sources.
• Cleaned, harmonized, and validated data; processed and stored it in Parquet format.
• Tracked data history and built business-focused fact and dimension models for traceable reporting.
• Automated data delivery with Python and Power Automate (desktop and cloud); used SharePoint for archiving and data access.
• Developed the Power BI solution from data preparation through to visualizing process statuses, work progress, and deviations.

Technologies: Python, SQL, Parquet, Power BI, Power Query, Power Automate, SharePoint, Copilot

AI implementation for retail, DACH

• Repositioning of the company and development of the Go-to-Market: target segments, Value Proposition and messaging architecture for the DACH retail market.
• Leadership of the brand and website relaunch across more than 100 pages, from Creative Direction and copy through UX to delivery.
• Development of the Demand Generation stack and redesign of the CRM: pipeline, lifecycle stages, lead scoring and reporting.

• 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.

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.

• 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

• 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

• 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.