CMake Expert

• Technical leadership across hardware, firmware, and software teams; scope: hardware/firmware team (4 people) and leadership group (5 people)
• Consolidated and documented a product family that had grown over more than 15 years and aligned it with CRA compliance — from the bare-metal I/O module to the cloud interface.
• Provided the most important customer product with the essential requirements and architecture documentation within two months — for a firmware landscape that had grown over more than 15 years. It now supports the customer’s modernization strategy.
• Established a monthly reporting line to the supervisory board and executive board within three months: nine meetings since 12/2025. The report itself is versioned and built from the CI pipeline; it is based on automatically collected activity and release data instead of assessments.
• Built a container-based CI/CD infrastructure from scratch: cross-compilation, host tests, and documentation builds in one continuous pipeline.
• Introduced declarative QA gates for DevOps and development artifacts — from the start using lefthook instead of pre-commit, executed in a dedicated container image.

Technologies used: arc42, req42, tpo42, docToolchain, PlantUML, ArchiMate, C4 model, ADR, C, C++ (GTest), CMake, Bare Metal (ARM Cortex-M3/M7), OCI containers, Jenkins, lefthook, Prometheus, Grafana, SBOM, CRA, OPC, SCADA, PLC integration, IPv6 migration, Zero Trust, Sociocracy 3.0, Cynefin

• Implementation of a full-stack application with Angular as frontend framework and Java as backend language
• Use of the Swagger OpenAPI specification for REST communication between frontend and backend applications
• Control of a card printer via the Nexus Card SDK framework
• Design and implementation of card management software with web interface and JavaFX module for printer monitoring
• Use of Cucumber tests for test automation and creation of test artifacts for testing outside the development environment
• Use of Wireshark for network investigations to analyze the API of a third-party product and to check the REST API of the self-developed software

• Analysis of the existing CAN communication between microcontrollers
• Analysis of the sensors used and the measured values collected
• Planning the CAN messages for transmitting the measured values
• Iterative adjustment of the microcontroller code to the new CAN messages
• Cross-compilation from x64 to arm64

• Architected and deployed end-to-end machine learning pipelines across classification and prediction datasets, ensuring robustness and reproducibility through MLOps best practices.
• Contributed directly to LLM model output accuracy improvement by designing and engineering specialised prompts grounded in end-to-end ML and SciML pipeline logic.
• Developed training data for large language models by formulating coding problems that models could not resolve and subsequently documenting the correct solutions.

• Built and configured a highly parameterized UVM environment to validate AMBA APB subsystem.
• Developed virtual sequencers to drive synchronized, parallel master-slave sequences ensuring accurate peripheral address decoding and protocol handshake.
• Methodologies: UVM, Constrained Random Verification
• Tools: Cadence Xcelium, SimVision

• Own the technical direction of several AI products in a product-owner capacity: shape roadmaps, guide the in-house development team, and provide oversight from concept through delivery.
• Act as the technical bridge between stakeholders, end clients, and vendors for a solutions provider (reseller and in-house products): evaluate vendor solutions against client needs, lead vendor discussions, and support sales and pre-sales with technical solution design.

• Development and validation of control concepts for grid stabilization with MATLAB/Simulink.
• Modeling of converters (VISMA), grids, and loads to study frequency and phase behavior during load steps.
• Analysis of the influence of inertia, damping, and controller parameters on stability, power output, and ROCOF.
• Development of adaptive control strategies to improve synchronization and dynamic grid support.
• Creation of automated simulation and evaluation tools to assess different scenarios and parameters.

Project: Intelligent Light Communication Software — Audi

• Analysis and clarification of system requirements with the customer and translation into software architecture and design decisions
• Architecture and implementation of CAN FD and SPI communication on NXP S32K312
• Design and development of flash bootloader, flash driver, and boot manager for secure OTA-capable updates
• Configuration of the AUTOSAR BSW architecture (Dcm, Dem, NvM, BswM, Os, Mcu, Port, Com stack, Rtc) for portability and maintainability
• Design of the crypto stack (Csm, CryIf, Crypto) for secure flash and diagnostic data; integration of the NXP HSE core and wrapper layer
• Integration of customer-specific modules (Sfd, Ivd, Npm) into the Vector AUTOSAR stack
• Definition of the memory architecture: Memmap, CMake, and linker script configuration
• Leading board bring-up for the Audi light demo platform; implementation of diagnostic routines and identifiers

• Development and maintenance of IT architectures with embedded Linux systems.
• Designing, implementing, and optimizing backend applications and script-based solutions.
• Analyzing and resolving issues, including troubleshooting and user support.
• Developing and implementing security concepts for cloud solutions.
• Administering networks (DHCP, DNS, NTP, VPN).
• Technologies: Linux, PowerShell, Bash, Python, Ansible, Kubernetes, GitLab CI.
• Methods: Kanban.

• Built and verified Zynq-7000 (Zybo Z7-10) FPGA prototypes in Xilinx Vivado – AXI IP integration, bitstream generation, hardware bring-up, timing-closure checks and waveform-based debug to confirm expected RTL behaviour.
• Set up Cadence Virtuoso schematic/simulation flows and documented settings, results and methodology for reproducible experiments – supporting structured verification and research documentation.
• Wrote Python automation for log parsing, structured data reporting and result analysis; worked daily in version-controlled Linux/Git workflows.

• Built a modular C++ 20 embedded Linux acquisition system on a Raspberry Pi, synchronizing IMU and dual-camera data streams to sub-millisecond accuracy.
• Integrated retro-reflective and contrast sensors to trigger acquisition and detect gaps between sorter rails.
• Implemented SPI & I2C sensor communication, GPIO interrupt handling with libgpiod, and CSV & JSON output.
• Designed a multi-threaded acquisition pipeline and an SPSC queue between acquisition and writer threads.
• Built a Python/HTML/CSS based web-server and validated the prototype in a DHL warehouse for defect detection.
• Documented software behavior, configuration, and results for maintainable handover and further development.

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.

• Embedded software development for EMS safety boards in medical technology according to IEC 62304 / ISO 13485
• Technologies: C++, OpenCV, Python, Qt6, JTAG, UART, CMake, IEC 62304, ISO 13485

Seqnaut and Sycosm (WIP) – Embedded Audio DSP & Synthesis Platform

• Embedded audio DSP framework — synthesizers, effects, drum machines; modular audio graph
• Sequencing: PianoRoll, StepGrid, MasterClock; 8-voice polyphonic synth; CLI + OSC
• Transient Detector — dual-envelope adaptive threshold, guitar attack detection
• Hardware: Teensy 4.1, custom AFE design tapping BOSS GX-100; MIDI FX integration

Label: C++23, C, Python, CMake, FreeRTOS, Teensy 4.1 (ARM Cortex-M7), Teensy Audio (Stoffregen), DaisySP, I2S/SAI, OSC, MIDI