IBRAHIM KADO
Technology Leader | Senior Principle Architect - Data & AI for In-Vehicle & Enterprise Solutions
"My passion is to bring AI into cars"
Bringing intelligent AI systems from concept to customer delivery across Porsche, Volkswagen, Audi, and CARIAD.
Stuttgart & Berlin, Germany
"Innovation starts with an idea, but must end with a product."
AI architect bridging in-vehicle Edge AI and enterprise cloud solutions—from LLMs running on Qualcomm NPUs to large-scale data platforms
Hands-on builder who delivers AI from concept to production, not just strategy decks
Board-level AI consultant translating complex technology into business value
Seeking senior leadership to scale in-car AI platforms and accelerate product delivery
My Approach
How I transform complex AI challenges into production-ready solutions
“Innovation starts with an idea, but must end with a product.”
- My guiding principle
Understand the Problem
Deep dive into the business context, user needs, and technical constraints. AI solutions must solve real problems, not chase technology trends.
Research & Analyze
Evaluate existing solutions, benchmark technologies, and identify gaps. Every great solution stands on the shoulders of proven approaches.
Architect the Solution
Design scalable, maintainable architectures that balance innovation with pragmatism. The best architecture is one that can evolve.
Build & Prototype
Hands-on development of MVPs and proof-of-concepts. I believe in touching the code, not just drawing diagrams.
Test & Validate
Rigorous testing in real environments - including in-vehicle validation. Quality assurance is not optional, it's fundamental.
Deploy & Iterate
Ship to production and continuously improve. Innovation starts with an idea, but must end with a product in customer hands.
Hands-On Builder
I write code, not just PowerPoints. Real understanding comes from building.
Business-Driven
Technology serves business goals. Every solution must deliver measurable value.
Quality First
In automotive, there's no room for 'good enough'. Excellence is the standard.
What I Offer
End-to-end AI solutions bridging in-vehicle Edge AI and enterprise cloud platforms
In-Vehicle AI Solutions
Edge AI for Automotive
On-Device LLM Deployment
Running Small Language Models on Qualcomm NPUs
Voice Assistant Systems
End-to-end ASR, LLM, and TTS pipelines on SoC
Vision-Language Models
In-cabin understanding with VLMs
Multimodal AI Assistants
Combining voice, video, and context
Hybrid Edge-Cloud Architecture
Seamless switching between on-device and cloud
Real-Time AI Inference
Sub-500ms latency for responsive UX
Enterprise AI Solutions
Cloud & Data Platforms
AI Platform Architecture
Scalable multi-agent systems and orchestration
Vehicle Data Platforms
Processing 2TB+ daily telemetry data
RAG & Knowledge Systems
Retrieval-Augmented Generation for domain knowledge
MCP & A2A Integration
Model Context Protocol and Agent-to-Agent communication
LLM Strategy & Selection
OpenAI, Claude, Gemini, Llama evaluation
Cloud Infrastructure
AWS, Azure, Google Cloud deployment
Edge AI Technology Stack
Hardware & Runtime
- Qualcomm NPU (SA8295P, SA8255P)
- QNN SDK & AI Engine
- ExecuTorch
- ONNX Runtime
AI Models
- Small Language Models (SLMs)
- Whisper ASR
- Vision-Language Models
- Custom TTS
Frameworks
- Android Automotive OS
- VHAL Integration
- LangGraph
- Koog AI Framework
Languages
- Kotlin
- Python
- TypeScript
- C++ (for optimization)
Consulting Services
From initial concept to production deployment
Requirements Analysis
Deep understanding of business goals, technical constraints, and user needs
Architecture Design
Scalable, maintainable system design with clear technical roadmaps
Hands-On MVP Development
Building working prototypes and proof-of-concepts, not just diagrams
In-Vehicle Testing
Real-world validation in actual vehicle environments
Quality Assurance
Automotive-grade quality standards and comprehensive testing
Ready to bring AI into your vehicles or enterprise?
Let's Discuss Your ProjectHigh level AI Architecture Vision
End-to-end AI flow from vehicle to cloud
In-Vehicle MCP
In-Vehicle AI
AI Platform
trator
Cloud MCP Servers
AWS
Azure
15+ Years of Innovation
Click each role to explore details and achievements
Technical Manager for AI, Edge AI and Vehicle Data
Lead Engineer & Technical Manager - Consulting Board on AI and Digital Assistants
Leading AI architecture strategy and multimodal AI assistant systems for next-generation Porsche vehicles.
Key Responsibilities
- Overall responsibility for the architecture of AI, cloud, and vehicle data platforms, supporting Software-Defined Vehicle capabilities and next-generation digital vehicle services
- Design and implementation of LLM-based hybrid assistant systems, combining on-device edge processing with cloud-based augmentation
- Development of AI-driven solutions for in-vehicle personalization, comfort, and intelligent cockpit interaction
- Architectural integration of embedded vehicle control and data interfaces, including VHAL and CarPropertyManager for vehicle function access
- Enablement of on-device AI execution on automotive-grade SoCs (e.g., Qualcomm Snapdragon), including Whisper-based ASR, TTS, and onboard LLM inference
- Design of a scalable in-vehicle AI platform to run onboard AI applications with secure connectivity to backend and cloud systems
- Cross-departmental coordination with Development, Sales, and Enterprise Management to ensure a holistic, customer-centric vehicle experience
- Advisory support to executive leadership and board-level stakeholders regarding AI strategy, digital assistant initiatives, and innovation roadmaps
Key Achievements
- Led the development of multimodal AI driver assistant integrating voice, video, and context understanding
- Successfully deployed production-ready LLM-based voice assistant on automotive-grade hardware
- Established AI architecture standards adopted across Porsche vehicle platforms
Technologies & Focus Areas
Lead Architect & Technology Advisor
Strategic consulting for Data and AI technologies. Designing and architecting data platforms on AWS for vehicle and customer data.
Presales Software Solution Architect
Architecture responsibility for Connected Car solutions enabling vehicle connectivity across Volkswagen Group.
Test Manager & Test Analyst
Test management for connected car web services across VW Group brands.
Software Automation, Data Engineer and Data Analytics
Data processing and research in the Lithium Battery field for electric vehicles.
Specialized Knowledge Areas
Click on any card to explore detailed expertise, projects, and technologies
Edge AI & NPU
On-device AI inference on automotive-grade SoCs
AI & ML Architectures
Large Language Models and multi-agent systems
AI Frameworks & Runtime
Qualcomm stack expertise for AI model deployment
Languages & Development
Full-stack automotive software development
Cloud & Data Platforms
Enterprise data architectures processing 2TB+ daily
Connected Car Services
Online personalization and digital services
In-Vehicle AI Stack
End-to-end automotive AI architecture from application layer to hardware acceleration. Highlighted areas represent my core expertise and hands-on implementation experience.
Applications Layer
Layer 1 of 4
AI Assistant
Multimodal voice & vision
Predictive Maintenance
Vehicle diagnostics
Battery Management
Optimization & monitoring
Personalization
Driver comfort & preferences
Gen AI Models & Frameworks
Layer 2 of 4
LLMs
GPT-4o, Claude, Llama
Edge Models
Whisper ASR, TTS, SLMs
AI Frameworks
Llama-Stack, ExecuTorch, ONNX
Model Lifecycle
Deployment & optimization
Operating Systems & Middleware
Layer 3 of 4
Android Automotive OS
AAOS platform
VHAL Integration
Vehicle HAL layer
CarPropertyManager
Vehicle control APIs
RTOS
Real-time systems
Hardware Layer
Layer 4 of 4
Qualcomm NPU
AI acceleration
GPU
Graphics processing
CPU
General compute
DSP
Signal processing
Memory
RAM & Flash storage
Core Expertise Across the Stack
Highlighted areas represent hands-on implementation experience and deep technical expertise
How to Build In-Car AI Powered Applications?
Building production-ready AI applications in vehicles requires deep expertise across the entire technology stack—from edge AI inference on automotive hardware to enterprise cloud infrastructure.
This end-to-end architecture represents my hands-on experience designing and implementing intelligent automotive systems, with highlighted sections showing where I've built production solutions at scale.
On-Vehicle Side
Infotainment Hardware + AAOS
Layer 1 - Software
Applications (Hybrid Execution)
Gen AI Models & Frameworks
Operating Systems & Middleware
Layer 2 - Hardware
Processing Units
Memory
Connectivity
Enterprise Infrastructure & AI Stack
Cloud Backend Services
Layer 1 - API & Orchestration
API Gateway & Management
MCP Servers (Model Context Protocol)
Layer 2 - AI/LLM Services
Cloud LLM Providers
AI Orchestration
AI Frameworks
Layer 3 - Data Services
Data Storage
Data Processing
Vehicle Data Platform
Layer 4 - Infrastructure
Compute
Security & Compliance
Observability
11 Registered Patents
Innovation protected through intellectual property across vehicle personalization, connected services, and data architecture
Method for Adapting Vehicle Component Settings
Method, computer program and device for adapting the settings of components of a means of transport. A secure protocol for adapting vehicle settings with condition-based license control.
Online Personalization of Vehicle Settings
Method for online personalization of vehicle settings and device for transmitting personalized vehicle settings to a backend server. Enables user preferences to transfer between vehicles with factory reset options.
Multi-Vehicle Functional Unit Adjustment
Method for adjusting a first functional unit of a first motor vehicle and a second functional unit of a second motor vehicle. Enables ergonomic settings synchronization across different vehicle types.
Transmission of Functional Parameters Between Motor Vehicles
Method for transmitting functional parameters between motor vehicles using neutral data format conversion. Enables seamless parameter transfer between vehicles of different types and configurations.
+ 7 additional registered patents in vehicle AI, data platforms, and connected services
Career Highlights & Impact
Transformative contributions across automotive AI, from concept to production
Multimodal AI Assistant for Porsche
Built state-of-the-art multimodal AI assistant on Android Automotive OS for Porsche vehicles, combining voice, text, and visual understanding.
Silicon Valley Startups
Co-founded 2 startups backed by Porsche and US-based UPLABS incubator, focusing on vehicle data analytics and GenAI technologies for automotive applications.
Online Personalization Launch
Successfully launched MOD3 and MOD4 online personalization features on MQB and MEB vehicle platforms across VW Group brands.
On-Device Voice Pipeline
Developed complete on-device pipeline: Whisper ASR, Small LLM, TTS, running entirely on Qualcomm automotive SoC with sub-500ms latency.
11 Registered Patents
Inventor of 11 registered patents in AI, automotive software, Edge computing, and connected vehicle technologies across multiple jurisdictions.
70+ Person SAFe Team
Successfully led cross-functional teams of architects and developers in agile SAFe setup on enterprise-scale AI and data initiatives.
Technology Partners
Working with industry leaders to deliver cutting-edge AI solutions for automotive applications
AWS
Cloud infrastructure and AI services
Google Cloud
Cloud platforms and ML services
Rivian
Electric vehicle technology
Azure
Cloud services and enterprise solutions
OpenAI
Large language models and AI
Education & Certifications
Academic background and professional credentials
Engineering Degree in Electrical Engineering
Saint Petersburg State University
Saint Petersburg, Russia
Specialization: Automation & Embedded Systems
Professional Certifications
Languages
Get in Touch
Interested in discussing AI strategy, vehicle technology, or leadership opportunities? I'd love to hear from you.
Contact Information
Connect with me professionally
automotiveaitech@gmail.com
Location
Stuttgart & Berlin, Germany