I am a Data Scientist | AI Architect & Engineer | Robotics & Mechatronics Engineer focused on designing intelligent systems using whatever technology the problem demands.

I specialize in the integration of AI, data-driven intelligence, and robotic systems, combining software architecture, machine learning, and engineering disciplines to build end-to-end intelligent solutions—from perception and decision-making to control and real-world deployment.

I have strong expertise in architecting AI-driven systems using modern architectural practices, including C4 Model–based system design, ADR-driven decision making, and architecture verification (ATAM). My work focuses on building scalable, secure, and cost-efficient AI platforms, particularly for GenAI, RAG-based systems, and multi-agent architectures, while maintaining high standards of quality, observability, and governance.

With a background in Robotics & Mechatronics Engineering, I bridge AI software architecture with physical systems, control logic, sensors, actuators, and hardware-aware constraints—enabling intelligent systems that operate reliably in real-world, dynamic environments.

• Programming Languages: Python, C/C++

• Frameworks & Tools: ROS, MATLAB, HTML/CSS/JavaScript, Flutter/Dart

• AI / Machine Learning: NLP, Computer Vision, Speech Processing, Tabular Data

• System & Software Architecture:

  • AI system design
  • Distributed systems
  • C4 Model (Context, Container, Component, Code)
  • API & backend architecture

• Design & Engineering: CAD, Mechanical & Hardware Design, Electrical & Computer Engineering

• Control Systems: Control Systems Engineering for Robotics

• AI & Software Architecture

  • C4 Model (Context, Container, Component)
  • High-Level & Low-Level Design (HLD / LLD)
  • Architecture Decision Records (ADR)
  • Architecture Tradeoff Analysis (ATAM)
  • API design (OpenAPI), integration patterns (REST, async messaging, AI protocols such as MCP)

• GenAI & Intelligent Systems

  • Retrieval-Augmented Generation (RAG, CAG, hybrid RAG, re-ranking)
  • AI Agents & Multi-Agent Systems (ReAct, Plan-and-Execute)
  • GenAI evaluation (faithfulness, relevance, latency)
  • Security for AI systems (OWASP Top 10 for LLM, guardrails)

• Data & MLOps Architecture

  • End-to-end data pipelines (ETL/ELT, Data Lake, Data Warehouse (DWH), Feature Store, Vector DB)
  • MLOps pipelines (training, deployment, monitoring, drift)
  • CI/CD, Infrastructure as Code (Terraform)
  • Model lifecycle management

• Infrastructure & Scalability

  • Kubernetes vs Serverless tradeoffs for AI workloads
  • High-availability (HA) and disaster recovery (DR)
  • Resource sizing (CPU, GPU, RAM, VRAM), inference optimization
  • Hybrid and multi-cloud AI architectures

• Governance, Cost & Leadership

  • FinOps-driven architectural decisions
  • Ethical & Responsible AI by Design
  • Observability (metrics, logs, traces)
  • Technical debt management and architectural governance

I design intelligent, production-grade systems that combine AI, robotics, and software architecture—balancing performance, scalability, safety, cost, and long-term evolution. My focus is on systems that think, decide, and act in real-world conditions, whether purely digital or cyber-physical.

If you’re looking for someone who can architect and engineer intelligent systems end to end—from requirements and risk analysis to AI + robotics production deployment—I’d be happy to connect:

• LinkedIn: View my LinkedIn profile