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Built Python-based AI microservices and integrations for an AEC/VR Unity-based SaaS app, focusing on LLM/VLM capabilities, retrieval-backed systems, RESTful APIs, containerized deployment, and an automation microservice for the CAD-to-Unity pipeline.

• Developed a custom Hybrid A* based algorithm in C# to simulate hospital scenarios and detect early-stage design conflicts from collision/spatial data and generate structured reports.
• Solved and automated the time-consuming problem of converting CAD files to usable Unity environments with a custom-engineered and real-time pipeline using a ZeroMQ-based communication layer to distribute workloads across multiple processes and achieve real-time performance.
• Built a Dockerized FastAPI pipeline for CAD-to-Unity automation, combining vision-based object matching, image embeddings, and precomputed metadata to automatically map CAD objects to Unity behavior scripts, assign properties, and reduce repeated AI inference calls.
• Created documentation and examples to help technical users understand, configure, and extend the AI automation pipeline.

Conversational AI assistant for cloud infrastructure and security queries

• Designed FastAPI backend with multi-turn conversation handler, token budgeting, and context window management.
• Integrated Amazon Bedrock (Claude 3 Sonnet/Haiku); built RAG pipeline with MongoDB chat history and semantic search.
• Implemented Factory Pattern for modular LLM provider switching; reduced model onboarding effort by 60%.
• Reduced LLM inference cost by 35% through model tiering (Haiku vs Sonnet) and prompt/entity consolidation.

Tech: Python, FastAPI, Amazon Bedrock, MongoDB, Streamlit, Pydantic.

• Led strategic software development of fusion algorithms for precise object tracking, trajectory prediction, and environment modeling based on multimodal sensor data (e.g., camera, LiDAR, radar, GNSS, IMU)
• Developed and implemented navigation algorithms for autonomous vehicles, including path planning, obstacle avoidance, and sensor fusion of visual, inertial, and distance-based sensor sources
• Automated extraction and training processes with CI/CD
• Developed and optimized data pipelines and processes in Microsoft Azure using Apache Spark, Databricks, and PySpark
• Developed and optimized embedded software for automotive control units
• Designed latency-critical software for real-time control in robotic systems with RTOS (freeRTOS, SAFERTOS)
• Used the Vector toolchain (CANdela, DaVinci, CANoe) for configuration and diagnostics
• Optimized existing data pipelines and processes (ETL, data warehouse, SQL)
• Developed and trained machine learning models using PyTorch
• Created deep-learning-based object detection and visual SLAM algorithms, trained on combined data from camera, LiDAR, and IMU sensors
• Implemented computer vision algorithms for object detection and classification in robotic systems using OpenCV and YOLO, utilizing synchronized image and depth data
• Implemented behavior-based control systems for autonomous robots using ROS2 Behavior Trees
• Performed testing, release, and integration of sensor fusion algorithms into automotive production programs
• Ensured adherence to proper software development processes and safety standards to guarantee high data quality (MISRA, ISO 26262, ASPICE)

• ▶ Built real-time voice assistant (STT → LLM → TTS pipeline) benchmarking and evaluating multiple STT providers including faster-whisper and Azure Speech. achieved sub-3s latency, Groq API (Llama 3) with multi-turn memory - directly handling edge cases in dictation, names and passcode recognition.

• Built a Python pipeline that converts lectionary web content into structured daily JSON, applying liturgical-calendar rules for accurate weekday and Sunday coverage.
• Shipped a read-only FastAPI REST API with shared Pydantic models and delivered a Kirundi-first web client for browser and mobile use.
• Owned the data layer and backend architecture, collaborating closely on system architecture and interfaces while automating refreshes with GitHub Actions and validating the ETL with pytest.
• Impact: Created a reliable, API-driven source of truth for daily Bible readings in Kirundi, enabling consistent access to previously unstructured content.

• Engaged by MILLA Group (autonomous shuttle manufacturer) to integrate and harden a safety-critical AD stack toward production: audited the architecture across perception, HD mapping, and positioning, and delivered a gap analysis with remediation roadmap.
• Lead root-cause analysis of sensor failures across a deployed shuttle fleet; shipped remediation in a versioned AD release and drove vehicle-level field validation at multiple operational sites.
• Design and implement interfaces between perception, localization, and vehicle systems in C++; identify integration risks and drive resolution of cross-subsystem technical issues across the AD stack.
• Standardized the client's software development lifecycle by introducing Agile workflows and CI/CD pipelines, shortening integration and validation cycles.

• Migrate company software to RHEL10
• Development in Bash, Python, C, Ansible

• Technical and professional management of software and ML development; largely independent implementation of programming and guidance of the team and external project partners
• Design, creation, and preparation of training and test data sets from experimental image data and simulations
• Selection, implementation, training, validation, and testing of neural networks for image-based reconstruction and transformation
• Systematic evaluation, comparison, and optimization of various model architectures (convolutional neural networks, generative adversarial networks, autoencoders, transformers)
• Design and implementation of explainable AI analyses for model interpretability and robustness assessment (analysis of feature maps, augmentation studies, guided backpropagation)
• Presentation of the developed methods and results in project meetings and at international conferences

• Development of a pilot system to control and monitor multiple GoPro cameras
• Implementation of start, stop, status, media, download, and diagnostic functions via COHN endpoints
• Realization of camera detection, single and group control, as well as stable session/keep-alive logic
• Setup of a download pipeline with queue, retry handling, and temporary files
• Consistent session, folder, and file naming for multi-camera recordings
• Integration of provisioning, certificates, and network operations

• Engineered production-ready Azure environments using Terraform, ensuring consistent infrastructure parity across VNets and Resource Groups
• Implemented Microsoft Fabric tenant and workspace architecture for multi-stage Medallion data processing pipelines
• Designed secure data pathways using Managed Private Endpoints for isolated Azure Storage access
• Managed Service Principals and authentication tokens for secure REST API integrations

• Supported the company's transition from an on-premise architecture to AWS cloud services, modernizing infrastructure and optimizing operational efficiency.
• Leveraged expertise in automation and software implementation to enhance scalability, reliability and profitability.
• Implemented Poetry and Ruff to streamline Python dependency management and code quality checks, improving development efficiency and reducing errors.
• Implemented an automated CI/CD strategy with GitHub Actions, which decreased deployment times and minimized manual intervention.
• Enforced deployment automation for Kubernetes, enhancing the scalability and reliability of applications across the organization.
• Evaluated and implemented Apache Airflow for workflow management, leading to more efficient scheduling and monitoring of data pipelines.
• Created data interfaces for energy traders, enabling them to optimize profit margins through improved data analysis and decision-making tools.

• Conceptualizing & developing a need-to-know, domain-based identity and access management system in a high-security environment
• Backend development (Python): API & microservice development

• Worked as a research associate in medical technology focusing on interoperability and system integration of medical devices
• Developed software solutions in Python to connect devices using the SDC11073 standardized communication protocol (Service-oriented Device Connectivity)
• Integrated and controlled distributed medical systems using service-oriented architectures
• Designed and implemented a service orchestrator for dynamic management of medical functions and data streams in a research project on mobile and nomadic networked healthcare systems

• Implemented a command line interface (CLI) for integration of REST APIs of various microservices for end users
• Centralized and simplified interaction with services through the CLI
• Implemented a REST microservice for custom data schemas based on an API-first approach
• Developed event-driven control with RabbitMQ to connect to other services
• Deployed services using Docker and Kubernetes and extended the CLI
• Managed complexity and data volume handling through the microservice