Cloud Computing Experts in Germany

As Germany’s only large integrated energy company, EnBW covers the entire value chain—from energy generation and distribution to serving customers. The company is expanding its renewable energy sources, working toward a socially responsible coal phase-out, and advancing key technologies such as the use of green hydrogen. A rapid energy transition and achieving climate neutrality by 2035 are priorities for EnBW.  Developing and implementing an end-to-end process view that takes both technical and organizational aspects into account  Ensuring end-to-end control of all IAM-related technical services  Establishing clear responsibilities and accountabilities across the IAM landscape  Working with various departments to identify and optimize an end-to-end architecture and act as the Single Point of Contact (SPoC) for Information Security  Introducing and monitoring governance policies to ensure compliance and security  Continuously improving IAM processes and systems through regular audits and service reviews  Taking part in external process audits as part of official audits against ISO standards  Further developing the policy that sets administrative requirements and procedures, and aligning it with administrative departments  Conceptually developing the KPI system for measuring process quality

• Taught ML, BI, and Big Data to Master's students.

Tech: Python, Power BI, SQL, ML, SnowflakeDB, databricks, MS Fabric, MongoDB, LLM

• Project: ESU Windows and SQL Server Consolidation / Configuration Management in ServiceNow
• Prepared an as-is analysis of all servers worldwide
• Prepared an as-is analysis of all SQL servers worldwide
• Conducted requirements analyses for SQL and server migrations
• Coordinated requirements with partners for migrations to Hyper-V (on-premises) or Azure Cloud
• Facilitated regular status meetings (Jour Fixe)
• Developed roadmaps and solution models for server migrations
• Set up test scenarios
• Facilitated workshops for the rollout of a global admin team
• Designed data models (CMDB) in ServiceNow
• Led workshops for the CMDB data model
• Developed solution models for the CMDB
• Created end-to-end configuration documentation and work instructions for the CMDB
• Prepared reports for license management
• Defined KPIs for data quality in ServiceNow
• Created a service catalog
• Facilitated workshops to define service requests
• Acted as interface between requirements analysis and the ServiceNow development team
• Systems used: Windows 7, Windows 10, Microsoft Office 365/2010, Windows Server 20xx, SQL Server 20xx, SharePoint, Azure Cloud, Hyper-V, ServiceNow, various tools

Project: Defect Generation on Test-Bench Images of Metal Surfaces Environment: Automated Visual Inspection (AVI), Metallurgy & Manufacturing

• Objective & Implementation: Designed, architected, and trained Generative Adversarial Networks (Pix2PixHD / SPADE) for image-to-image transformation. Targeted generation of synthetic material defects (e.g., cracks, inclusions, scale) on rough metal surfaces under real test-bench lighting conditions for privacy-compliant and efficient dataset expansion (data augmentation).
• Technical Design: Implemented robust Generative AI and computer vision pipelines in Python and PyTorch. Used semantic segmentation approaches for mask-controlled defect synthesis and subsequent evaluation with EfficientDet object detection models.
• Business Impact: Massive dataset upscaling (10x) without time-consuming and costly physical test-bench runs, while significantly improving the detection performance of automated inspection systems.

Technologies & Skills Used: Python | PyTorch | SPADE | Pix2PixHD | EfficientDet | Machine Learning | Semantic Segmentation | Computer Vision

• Administration and further development of the M365 environment, including Teams, Exchange Online, Intune, and SharePoint Online
• Development of dashboards for performance monitoring with Microsoft Power BI
• Implementation of user requirements and processes with low-code/no-code technologies (Power Apps, Power Automate)
• Use of Jira and Azure DevOps to plan and implement user stories in an agile project context
• Participation in daily stand-ups, sprint planning, sprint reviews, and retrospectives as the technical point of contact
• Planning and implementation of security policies using Azure Conditional Access and multi-factor authentication
• Configuration and deployment of clients and applications via MECM (SCCM) and Baramundi

• Project: Thermomix Online Mock
• Manual execution of functional tests
• Implementation of automated end-to-end tests
• Execution of regression tests and analysis of results
• Further development of the QA website server using Express.js, Handlebars and Node.js
• Further development of the test environment
• Technologies: Agile software development Scrum, Robot Framework, Python, JavaScript, Git (GitLab), VS Code, Jira, Confluence, Express.js, Handlebars, Phoenix/Elixir

Tools: Fabric, AWS, dbt, Power BI, SQL, DWH, R, Python

• Supported customers in implementing an architecture design for extracting and preparing data
• Planned the design and implementation of the BI and DWH platform
• Ensured the scalability and performance of the data platform

• Expert-supervised AI systems for scientific reasoning, model evaluation, and research workflows.
• Built the IAS Problem Solver, an orchestrated system for difficult mathematical reasoning; it achieved 84% in one submitted answer set on the Leipzig mathematics benchmark.
• Built a resumable state-machine pipeline for research-grade mathematics benchmark generation: source selection, LLM-agent-based phenomenon discovery, task synthesis, gold-answer and certificate generation and validation, probing, repair, human feedback, and quality gates, targeting tasks that are difficult, natural, verifiable, and cost-effective.
• Current work extends this into budget-aware AI research workflows for real scientific problems with expert review.

Tech stack: Python, OpenAI/OpenRouter-compatible APIs, embeddings, RAG, SQLite.

IOG (IOHK), is one of the world's pre-eminent blockchain infrastructure research and engineering companies.

• Converted a lingering R&D project into a cohesive, production-ready testnet; built and scaled the 35-member engineering team (Core, QA, SRE) to achieve this goal.
• Defined strategic direction and aligned technology development with business objectives as a key member of the leadership.
• Optimized software development processes and implemented agile methodologies, enhancing operational efficiency and code security.
• Delivered projects in a fast-paced startup environment through effective project management and resource allocation.

• 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.

• Linux server migrations: Planning and implementation of the migration with SLES Linux Deployment of VMs in VMware 8.0
• Guiding colleagues in configuring Linux VMs in vSphere Auto Deploy
• Application operations: Ensuring the smooth operation of applications on the migrated servers
• Operations manuals: Revising existing operations manuals, adding to them and creating new ones when required
• Reviewing service offerings: Adjusting and optimizing the service offering of external service providers
• Logistics SW, RedHat Linux, Ansible, Confluence / Jira

• PRISMA project
• Ansible automation
• Windows third-level support for Windows NT, Windows 2000, Windows 2013, Windows 2016, Windows 2019

• Migration of existing data jobs from Cognos Data Manager to Tibco/IBI Datamigrator
• Migration data jobs parametrisation for dynamic runs
• Optimisation and cutting-back
• Regression tests
• Knowledge transfer and documentation

• Responsible for driving digital transformation and aligning country organizations with the Rhenus platform model

• Initiated the digital transformation roadmap for five countries, ensuring alignment with global group strategy

• Built and led a high-performing digital transformation consulting team, expanding delivery capacity from one to three value streams and thereby fast tracking the roadmap from 3 to 2 years

• Acted as strategic advocate for 5 country organizations, ensuring group-wide cross-functional alignment

• Redefined business analysis into an agile approach, reducing time-to-value for platform harmonization by 50%