Senior/Lead Architect (Hands-On)

5/2024 – 10/2024

Defining and implementing an efficient, scalable backend microservices infrastructure for a AR/VR solution. Enable AR/VR clients to connect to the backend infrastructure including 3rd party APIs. Analyzing/driving requirements and implementing the respective backend features. Preparing the setup for a planned Kubernetes-based deployment.

Integrating a complex WebRTC microservice to provide real-time audio, video and data connectivity for a significant number of users. Connecting Unity clients with the WebRTC system. Defining and implementing additional microservices to manage users, VR related content, system notifications. Implementing various data translation/marshalling logic. Setting up a complete observability platform managing logs, traces and KPIs/metrics.

Exploring options for a variety of use cases including the usage of AI Agents, LLM models and NLP solutions. Pushing things forward with the small and young team and providing know-how transfer.

Main tech gear: Golang, WebRTC, Livekit, Pion, PostgreSQL, Docker, docker-compose, Kubernetes, Rancher, Azure, Grafana, Prometheus, Jaeger, OpenTelemetry, Unity, Meta Quest (Pro), NATS, Typescript, Angular

Postgresql, Docker, Go (Programmiersprache), Angular

4/2023 – 4/2024

Lead the design and development of an industrial real-time video analysis infrastructure for a Gigafactory/Battery project with the main target advanced and flexible manufacturing video analytics.
Pushed the implementation of Proof of Concepts (PoCs) for core software components, serving as foundational blueprints for the development team and ensuring alignment with project specifications. Implementing many PoCs/Modules as "hands-on" Architect myself and then handed over to the team.
Directed a global remote development team, driving collaboration and knowledge sharing across borders to drive the project towards success.
Engaged with a wide array of internal stakeholders to gather requirements, refine project objectives, and develop a comprehensive system architecture that addressed key business needs.
Produced extensive documentation, including system designs, Jira epics, and task outlines, facilitating clear communication and efficient workflow within the development team. Led the deployment phases with a focus on end-to-end (E2E) testing, ensuring the system’s reliability and performance met high standards.
"Hands-On" developed and demonstrated versatile use case implementations in Golang and Java (Quarkus), focusing on monitoring, data storage (S3, MinIO, SeaweedFS), and event streaming (Kafka) to guide the team’s development efforts.
Conducted in-depth analysis of cutting-edge machine learning technologies, including convolutional neural networks (CNNs), visual transformers, and localized natural language processing (LLMs), to explore potential enhancements for the video analysis capabilities.
Defining and implementing the "Observability" platform using Prometheus, AlertManager, CAdvisor, Grafana, Jaeger, OpenTelemetry, fluent-bit.

Tech Stack: Kafka, Jaeger, Open Telemetry (OTel) ,Prometheus, Grafana, PostgreSQL, MinIO, SeaweedFS, Quarkus, sFTPgo, Java, Python, Golang, Docker, AWS, Machine Learning, OpenCV

Java-Entwickler, Architektur (allg.)

1/2022 – 1/2023

Defined and implemented the end-to-end architecture for real-time video and data streaming. The solution was optimized for an autonomous robotic system in the consumer market, enabling advanced automation in smart home environments.
Helping to integrate the resulting solution within BSH's existing HomeConnect cloud ecosystem, leveraging the platform to extend the system's capabilities.

Implemented multiple Proof of Concepts (PoCs), each targeting distinct real-time video and data streaming scenarios, setting the stage for a flexible, multi-use architecture. Working on the full-stack development of a WebRTC-based communication layer, enabling real-time interaction between the robotic system and the end-user interface.

Defined the scope and architecture for and implemented a TypeScript-based WebRTC client for automatic system testing, alongside a Golang/gstreamer powered edge device client for streamlined operations. Added a real-time remote control data channel, coupled with a highly flexible command and control structure, ensuring precise and safe manipulation of the robotic unit.

Defined and applied a comprehensive suite of metrics and key performance indicators (KPIs), providing a framework for continuous system evaluation and improvement. Developed a suite of flexible diagnostic tools aimed at analyzing video quality, ensuring the highest standards were met for user experience.

Delivered a strategic approach to incorporating potential machine learning techniques, defining requirements to advance the system's decision-making and predictive capabilities. Leading the development team based in India, managing project deliverables, timelines, and ensuring the adherence to quality and technical standards.

MQTT/Kafka, Docker, Quarkus, Prometheus, Grafana, PostgreSQL, Cassandra, WebRTC, Nvidia CUDA, Tensorflow, Angular 12+ UI, Ionic mobile apps, Test Tools, Jira, Confluence, RPi, Jetson Nano, Qualcomm CPUs, Pion, Livekit, embedded hardware, Sensors&Actuators, ROS2, AWS DeepRacer, Go/Golang, Typescript, Shell Scripts. OpenTelemetry (OTel), Grafana, Prometheus

Tech Stack:
MQTT/Kafka
Docker
Quarkus
Prometheus
Grafana
PostgreSQL
WebRTC
Nvidia CUDA
Tensorflow
Angular 12+ UI
Ionic mobile apps
Test Tools
Jira
Confluence
RPi
Jetson Nano
Qualcomm CPUs
WebRTC
Pion
Livekit
embedded hardware
Sensors&Actuators
ROS2
AWS DeepRacer
Go/Golang
Typescript
Shell Scripts
OpenTelemetry

Postgresql, Backend, Golang, Robotics