it's me

About Me

"Building and validating embedded systems that meet real-time constraints."

Hi, I'm Chibundu, an Embedded Systems Integration & Validation Engineer and a dual Nigerian–German citizen with full EU work authorization, based in Stuttgart. I work across automotive ECUs, ARM, TriCore, and STM32, and system software validation. I integrate firmware, diagnostics, middleware, and hardware-software interfaces using C/C++ and Python across Linux, RTOS, and bare-metal environments. My work combines AUTOSAR and diagnostic expertise with system integration, runtime analysis, validation, platform engineering, and AI-assisted engineering automation.

What I do: System integration, embedded validation, runtime analysis, and engineering automation

"From ECU diagnostics to platform validation and AI-assisted embedded engineering."

Education

  • M.Sc. Automotive Software Engineering

    Chemnitz University of Technology

    2019 - 2021

    Thesis: Embedded System Optimization of Radar Post-processing in an ARM CPU Core

  • B.Eng. Electronic Engineering

    University of Nigeria, Nsukka

    2011 - 2016

    Final Year Project: LED-based electronic notice board controlled via Android phone

Experience

  • Embedded Software Development Engineer

    Vector Informatik

    May 2022 - Present

    Collaborated with Mercedes-Benz as Diagnostics Feature Owner for a base-layer project, alongside ECU and software integration, AUTOSAR diagnostics (DCM/DEM/DoIP), generated-code and runtime analysis, validation, automation, and cross-layer root-cause analysis.

  • Embedded Software Developer

    Gliwa Embedded System

    Nov 2021 - Apr 2022

    Build infrastructure improvements (GNU Make), unit tests for validation.

  • Embedded Software Intern / Thesis Work

    Hensoldt

    Nov 2020 - Oct 2021

    ARM Cortex-A53 signal processing optimization; legacy C/C++ improvements; ~30% optimization.

Citizenship & Work Authorization:Nigerian • German • EU work authorization
Focus:System integration • validation • platform engineering
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Tooling:C/C++, Linux, RTOS, CI/CD, Python
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Domains:Automotive ECUs • Embedded Validation • IoT • Embedded AI

Professional profile

Embedded systems, integration, validation, and intelligent tooling

A broader engineering profile built on deep automotive diagnostics experience and expanded through platform integration, runtime verification, embedded software, and automation.

Core Expertise

Embedded Systems Integration • Automotive Diagnostics • AUTOSAR Classic • System Validation • Cross-Layer Root-Cause Analysis • Configuration-Driven Software

Automotive & Embedded

AUTOSAR Classic • UDS/OBD • DCM • DEM • PduR • CanTp • DoIP • SoAd • BswM • FiM • CAN/CAN-FD • LIN • Automotive Ethernet • SOME/IP • ECU Integration

System Engineering & Validation

System and Software Integration • Interface and Dependency Analysis • Runtime Behaviour • Integration Testing • SIL/HIL Concepts • Requirements-Based Testing • Failure Reproduction

Embedded Software

Embedded C/C++ • Python • ARM • TriCore • STM32 • FreeRTOS • Linux • Interrupts • Timers • PWM • ADC • UART • I²C • DMA • Firmware Debugging

Engineering Tools & DevOps

CANoe • CANalyzer • DaVinci • Trace32 • GDB/OpenOCD • Git • Jenkins • CI/CD • Docker • QEMU • Yocto Concepts • Automated Test and Build Environments

AI & Engineering Automation

Local LLMs • Ollama • Python AI Applications • AI Agents • MCP Architecture • Tool-Using LLMs • Context Management • SQLite • Retrieval Systems • AI-Assisted Engineering

Developing expertise / engineering research

Embedded Software Analysis & Runtime Verification

Exploring ELF-based software analysis, runtime execution tracing, function-level simulation, and standards-based verification for hardware-independent embedded software validation.

ELF binary analysis
Function dependency and call graphs
Runtime execution tracing
Hardware-independent software simulation
Standards-based runtime verification
AI-assisted embedded debugging

Engineering Workflow

"From reproduction to resolution: a systematic approach to embedded challenges."

Decompose & Reproduce

I translate broad system issues into testable engineering questions, reproduce the behaviour, map component dependencies, and define what correct behaviour should look like.

Trace Runtime Behaviour

I trace configuration, generated code, interfaces, execution flow, timing, memory, and state transitions across application, middleware, OS, and hardware boundaries.

Isolate the Root Cause

I use a hypothesis-driven approach with logs, CANoe/CANalyzer, GDB, Trace32, OpenOCD, and QEMU, then confirm the cause with targeted tests.

Validate Against Intent

I compare behaviour with requirements, interfaces, and standards, then turn reproducible scenarios into Python or C/C++ unit, integration, SIL/HIL-oriented, and CI tests.

Improve the Platform

I address interface, reliability, and performance constraints through architecture changes, firmware fixes, NEON vectorization, loop reduction, or compiler strategy.

Automate & Deliver

I deliver fixes, test evidence, engineering tools, and clear documentation, using Python, CI/CD, and AI-assisted workflows where they improve repeatability.

Engineering strengths

"Embedded integration, validation, diagnostics, and automation across the software stack."

Embedded System & Software Integration90%
Automotive Diagnostics & AUTOSAR90%
System Validation & Root-Cause Analysis90%
Embedded C/C++ • Linux • RTOS85%
Python Engineering Automation80%
DevOps • CI/CD • Docker • QEMU80%