NVIDIA Jetson Experts in Germany

• Building strong awareness within the company around nearshoring
• Engagement Manager in the Nearshore Competence Center
• Responsible for nearshore consulting, partner screening and technical onboarding, designing and implementing cooperation scenarios, change management, stakeholder management, participation in steering committees, and collaboration with IT and business units
• Tools used: Microsoft Office 365, Microsoft Teams, Azure Devops, Microsoft Sharepoint, Conceptboard
• Key results: Establishment of a nearshoring strategy, successful identification and implementation of outsourcing partnerships, delivery of change management and stakeholder management at the highest level

• TrendReel, production LLM agent and RAG system (Python, LangChain, OpenAI, Groq/Llama 3, Claude, FastAPI, Kubernetes, PostgreSQL).
• Designed and built a production multi-step LLM agent system: a script generation agent with a per-platform psychology database, 7 viral narrative frameworks, and structured quality scoring, switching between Claude and Groq backends in real time based on output metrics.
• Implemented multi-provider LLM routing (Claude primary, Groq/Llama 3 fallback) with priority-chain failover and quality-based provider switching, achieving 95% inference cost reduction while holding measurable quality thresholds.
• Built an advanced RAG-style retrieval pipeline with per-platform knowledge bases, semantic content matching, and structured output evaluation across 7 decision frameworks, directly analogous to multi-tenant context-based reasoning for enterprise document workflows.
• BrainyAI, adaptive AI learning platform (Python, LangChain, Groq Llama 3.3-70B, OpenAI, Next.js, Supabase, Redis).
• Integrated Groq Llama 3.3-70B with education-level-aware prompting, dynamically adjusting vocabulary depth, citation complexity, and reasoning style across four student proficiency tiers.
• Nexus Prime, multi-tenant SaaS platform for marketing and growth automation (25 modules, 99 backend routers, 153 frontend files).
• Built a 25-module, 99-router multi-tenant SaaS platform covering ad remix, affiliates, WhatsApp inbox, email, and cart recovery, serving four subscription tiers from $199 to $1,999 per month with integrated Stripe, Paystack, and Flutterwave billing.
• AI Video Surveillance Platform, multi-tenant edge and cloud computer vision system currently in active client pitch.
• Designed a multi-tenant AI video surveillance platform combining edge YOLO26 inference on NVIDIA Jetson Orin NX boxes with a central GKE cloud layer (Postgres, Pub/Sub, ClickHouse, R2, Keycloak) for event storage, dashboards, alerting, and multi-tenancy.

• Developed a real-time video analytics proof-of-concept for deployment on NVIDIA Jetson edge devices.
• Implemented DeepStream pipelines including object detection, tracking, human pose estimation, face anonymization, and zone intrusion detection.
• Built a Qt/Python demonstration UI interfacing with the AI pipeline via REST APIs.

Leading the end-to-end development of Edge AI-powered smart glasses for visually impaired individuals, aligning product vision with user needs and managing a cross-functional team of data scientists, Android developers, AWS engineers, and hardware specialists.

• Defined product roadmap for Edge AI smart glasses and MVP features through user research, stakeholder interviews, and competitive analysis, ensuring accessibility and real-world usability.
• Developed and validated a PoC for AI-driven cancer cell identification in PET/CT scans, collaborating with medical experts to optimize diagnostic accuracy and clinical relevance.
• Built and scaled a multidisciplinary team of 75+ engineers, interns, and designers across Germany and India, driving cross-border collaboration and iterative prototyping.
• Established strategic partnerships with NGOs, healthcare providers, and advocacy groups to embed inclusivity and patient feedback into product design.
• Drove hands-on hardware-software integration using Raspberry Pi and Jetson Nano of AI models. Initiated and nurtured relationships with suppliers, manufacturers, and ecosystem players to build scalable go-to-market plans.
• Owned critical product decisions, from prototype development to funding strategy, applying a data-informed and impact-driven mindset.
• Fostered a learning-focused culture by facilitating brainstorming sessions and continuous feedback loops between engineering and product.

Achievements:

• Public speaker: Auto.Ai 2025 (Berlin), Wearable technologies 2025 (Munich and Bangalore), MEDICA 2024 (Dusseldorf)
• WMF, Bologna, Italy (June 2024): Only AI startup to be selected from Germany as EBV hero to represent sprhava on global platform
• Medica, Germany (2024): Delivered a speech on AI smart glasses in world's largest Healthcare event.
• Wearable Technologies, Bengaluru, India (Dec 2024): I was a speaker presenting sprhava and its product.
• Venturise Global Challenge (GIM 2025, Bengaluru Palace, Karnataka): sprhava was selected as one of the 16 top startups (ESDM) to present on this global platform
• Wearable Technologies Conference 2025 EUROPE, Munich, Germany (May 2025): Delivered a talk on Edge AI at the Europe's biggest wearable tech event.
• InsurNext Köln, Germany (2025): sprhava was honoured with a booth from Cologne administration.

Development of a route planner for incident communication.

• Development of the REST API
• Set up a patch system for maintaining the routing graph
• Expansion of the testing infrastructure
• Performance and memory optimization (JMeter, JFR)

Technologies: Java 21, Spring Boot, JGraphT, Flyway, MapStruct, Caffeine, ShedLock, JMeter, Kubernetes, JFR

• Automated driver assessment by programming temporal rule engines to evaluate lane-change execution safety, head-pose mirror checks, indicator usage cycles, and compliance with traffic lights and road signs
• Synchronized real-time traffic sign recognition and multi-state traffic light classification models with time-series CAN-bus telemetry and HD-map spatial priors to grade traffic rule adherence
• Trained and deployed distinct deep learning models optimized for interior cabin monitoring and exterior surrounding-area perception
• Combined perception outputs with camera intrinsics and horizon stability checks to execute 3D ground-plane object distance estimation assuming flat-ground geometry
• Deployed a split-compute edge network across a 10-vehicle fleet via VPN, implementing a zero-allocation host memory pipeline to eliminate frame accumulation latency (6×21 FPS per vehicle)

Technical audit for scientific software.

• Implemented data/feature pipelines and automated validation/reporting for multi-million-row insurance datasets.
• Built production-grade image processing to detect fabric defects; delivered maintainable, well-tested Python code and concise reports.

• IT consulting, coaching, and implementation with a focus on AI

• Computer vision engineer responsible for development of industrial vision solutions, beginning as a working student and transitioning to a full-time role in May 2025.
• Designed and implemented vehicle detection and counting models; integrated the pipeline into a cloud-deployed system (Azure) that delivers live analytics dashboards.
• Building an offline print quality assurance system that scans corrugated-board prints on production lines to detect and classify defects such as splashes, impurities and colour deviations, deploying the solution on Jetson edge devices.
• Collaborated with cross-functional teams while focusing on computer vision components, containerization, and deployment.

• JAVA development for thermal printer test program

• Further development of the free thermal printer test program in Java 1.8 AWT and Swing

• Creating new plugins for sensor feedback using a real-time bar chart

• Using multiple printer languages for USB, UDP, TCP and RS232 communication

• Improving usability and responsiveness with threads and string buffering

• Querying and displaying network configuration

• Converting and processing hex data from printer responses

• Advanced study of servomotors and USB bus

• Enumerating available USB ports from the Windows Registry, retrieving additional information via PowerShell, parsing and listing all in a Java list box

• Fixing reported database errors

• Detecting if the printer driver is installed and recognizing physically connected devices

• Migration to Windows 11

• Handling customer tickets as part of support in C++ and Qt6

• Writing CMake scripts

• Compiling STM32 printer firmware with CMake and managing the process in FileMaker Pro

• Technologies: Eclipse, Java 1.8, AWT, Swing, RS232, USB, TCP, UDP, PowerShell, servomotor technology, Windows 10 and Windows 11, WSL 2.4, Ubuntu Linux, CMake, Qt6, FileMaker Pro

• Developed AUTOSAR applications using Eclipse RCP for RTA-CAR AUTOSAR stack from ETAS
• Collaborated with Platform and Isolar-A teams on ASW development and testing workflows
• Implemented UI automation testing using Java SWTBot framework, enhancing regression coverage
• Built microservices-based applications using Java, Spring Boot, and Angular for internal tooling
• Enhanced AUTOSAR toolchain reliability through cross-team collaboration in development and testing

• Developed LLM-based automation utilities including structured reasoning pipelines, LLM-as-a-Judge evaluation tools, and multi-model comparison frameworks.
• Built RAG pipelines for internal research workflows using LangChain, ChromaDB, and FastAPI, enabling semantic retrieval and multi-step reasoning.
• Integrated LLM microservices into existing ML systems using Docker, FastAPI, and GitLab CI/CD with reproducible deployment workflows.
• Designed inference APIs combining vision models and LLM reasoning for multimodal analytics and decision-making.
• Optimized embedding-based retrieval using vector store pruning, improved chunking logic, and dynamic retriever selection.
• Performed prompt engineering and system instruction tuning for consistency, robustness, and reasoning quality.
• Built benchmarking suites to evaluate LLM latency, reasoning quality, retrieval accuracy, and robustness under different prompt templates.

• Developed a Python-based synthetic data generation pipeline in Blender to simulate complex human-forklift interactions for robotic perception and AI model training.
• Designed and modeled 3D industrial digital twins to support depth estimation, stereo vision, and safety analysis workflows.
• Collected and processed LiDAR, laser, and photogrammetry point clouds to generate accurate 3D maps for environment reconstruction and ground-truth data creation.
• Developed and deployed YOLOv8-based pose estimation and depth perception algorithms using PyTorch and OpenCV, optimized for GPU clusters and NVIDIA Jetson platforms.
• Integrated and validated AI modules in ROS-based robotic environments, ensuring real-time performance and interoperability.