Role: ICT Infrastructure & Systems Specialist

Currently fulfilling mandatory military service with a specialization in mission-critical network systems. I am responsible for the operation and maintenance of the Tactical C4I (Command, Control, Communication, Computer, and Intelligence) infrastructure, specifically the ATCIS (Army Tactical Command Information System).

Key Responsibilities:

• Network Administration: Maintaining high-availability secure internal networks (Intranet) and troubleshooting hardware/software failures in a high-security environment.
• System Maintenance: Managing server hardware and communication terminals to ensure 24/7 operational readiness during tactical exercises.
• Crisis Management: Developing resilience and rapid problem-solving skills by maintaining communication links under simulated combat pressure.

Role: Internal AI Tooling Engineer

Led the development of a secure, internal LLM assistant for a 50-person organization, bridging the gap between enterprise security needs and generative AI capabilities.

Technical Stack: Python (FastAPI, PySide6), SQL Server (SQLAlchemy), LangChain, OpenAI API

Key Engineering Achievements:

• Secure AI Architecture: Built a Windows desktop client (PySide6) coupled with an always-on FastAPI backend, enabling employees to access internal data (news, Excel, fund docs) securely.
• Governance & Audit System: Implemented a robust Role-Based Access Control (RBAC) system with versioned client distribution. Engineered comprehensive audit logging (usage, IP, MAC address) to meet financial compliance standards.
• Leakage Prevention: Developed a keyword-based risk detection system (Grade A/B/C thresholds) that triggers admin alerts to prevent sensitive data leakage.
• Prompt Engineering Library: Deployed a curated library of ~10 prompt templates with attribution and moderation features to standardize AI usage across the firm.

Role: Serverless Backend Engineer

Responsible for building scalable REST endpoints and serverless data pipelines to support the platform’s core functionality.

Technical Stack: Node.js, TypeScript, AWS (Lambda, AppSync, DynamoDB), GraphQL, Jest

Key Engineering Achievements:

• Serverless Pipeline: Implemented ~10 REST endpoints and complex data flows using AWS AppSync and Lambda, ensuring high availability and scalability.
• Ops Streamlining: Optimized backend operations via GraphQL, allowing for more efficient data fetching and reducing over-fetching issues on the client side.
• Test-Driven Development: Shipped comprehensive unit and integration tests using Jest, significantly improving code reliability and reducing regression bugs in production.

Role: Embedded Systems Mentor

Guided high school students in advanced robotics concepts, focusing on code reliability and autonomous systems.

Key Achievements:

• Autonomous Reliability: Mentored 9 students in embedded programming, sensor fusion, and motion planning algorithms, resulting in a 93% success rate for autonomous routines during competition.
• Technical Education: Taught best practices in version control and debugging for embedded C++ environments.

Role: Creative Engineering & Prototyping

Started my engineering journey at one of the world’s most innovative YouTube channels. Contributed to the rapid prototyping of functional sci-fi concepts.

Key Achievements:

• Rapid Prototyping: Assisted in the mechanical design and firmware coding (C++) for various high-power prototypes.
• Problem Solving: Thrived in a fast-paced environment where “fail fast, fix faster” was the daily mantra.

Role: 6G Simulation Engineer

Contributed to the research and development of next-generation network simulations, integrating C++ logic with Python-based workflows.

Technical Stack: C++14 (Boost), Python, PyQt, Unreal Engine, CARLA Simulator

Key Engineering Achievements:

• Simulation Integration: Developed high-performance internal APIs using C++14/Boost that were callable from Python, enabling seamless integration with a CARLA server for autonomous driving network simulations.
• Visualization Tools: Built a PyQt GUI to monitor and control Unreal Engine simulations in real-time, improving the research team’s workflow efficiency.
• Ray-Tracing Implementation: Implemented custom ray-tracing logic within the CARLA simulation context to model 6G signal propagation more accurately.

Role: Industrial AI & Systems Developer

Focused on optimizing manufacturing processes through computer vision and efficient machine communication protocols.

Technical Stack: Python (Qt, PyTorch, OpenCV), Jetson Nano, PLC protocols

Key Engineering Achievements:

• Communication Optimization: Reduced PLC Host communication overhead by ~30% by implementing a custom caching mechanism, significantly speeding up data throughput.
• Edge AI Deployment: Built and deployed a lightweight Artificial Neural Network (ANN) model on Jetson Nano edge devices. This reduced server load and improved defect detection response times.
• Tooling Suite: Developed a suite of GUI, ML, and telemetry tools using Python (Qt) and OpenCV to support shop floor operations.