Description

I am an Embedded Systems & AI Specialist bridging the gap between physical sensors and cloud intelligence. Holding an MSc in Internet of Things (Merit) from the University of Southampton, I provide a "Full-Stack Hardware" approach to modern engineering challenges. While many developers focus solely on software, I bring a distinctive advantage: applying AI/ML as an intelligence layer on top of physical hardware, enabling embedded systems to make real-time, autonomous decisions from sensor data.

Core Expertise

Edge AI & On-Device Inference: I specialize in deploying machine learning models and LLM agents directly onto resource-constrained hardware (STM32, Raspberry Pi) to reduce latency and enhance privacy.

Digital Logic & FPGA Design: Expert in RTL coding and SystemVerilog for high-speed signal processing, including custom RISC-based processor design on Intel Cyclone V.
Hardware Security: Experienced in implementing AES and cryptographic security layers for private enterprise AI deployments, ensuring data integrity across system boundaries.

End-to-End Prototyping: Certified in full PCB fabrication—from KiCad schematic capture and multi-layer layout to SMD soldering and bench-instrument debugging (oscilloscopes, signal generators).

Proven Project Success

Medical Tech: Developed an AI-enhanced patient monitor using FreeRTOS and ARM Cortex-M, integrating real-time ML for anomaly detection.

Silicon Acceleration: Built a 5-point convolution processor in hardware to accelerate AI computations directly in silicon.
Enterprise Security: Architected secure, scalable AI deployments on cloud infrastructure for startups, focusing on deterministic performance.

Compliance & Professionalism

Location: Based in Southampton, UK.

Right to Work: Graduate Route Visa.

Security: Eligible for NSV Clearance.

Memberships: Member of the IEEE.

Languages

English
Native or bilingual
Hindi
Native or bilingual

Workplace preferences

Can work on-site

London (up to 50km)

Sia HP Technologies
AI Security Specialist / Security Systems Engineer
March 2026 - Today (3 months)
• • Architecting secure, private LLM deployments for enterprise clients, applying hardware security principles to enforce strict model-boundary controls.
• • Implementing AES encryption and cryptographic boundary enforcement to guarantee data integrity across AI inference pipelines.
• • Designing deterministic, resource-constrained AI deployments on cloud infrastructure, reducing compute overhead while maintaining response guarantees.
Cryptography LLM
Freelance
System Logic & Backend Architect
October 2024 - March 2026 (1 year and 5 months)
Southampton, UK
• • Translated complex stakeholder requirements into detailed technical specifications for an AI-driven medical platform, bridging clinical and engineering teams.
• • Designed backend architecture and data-mapping pipelines using Agile/DevOps workflows, accelerating delivery cycles.
• • Built regulatory-grade data validation pipelines that measurably reduced integration defects ahead of clinical testing milestones.