Engineering journey

• Built a Google ADK pipeline that extracts and classifies procurement documents in production, feeding insights into downstream agent workflows and the memory system.
• Designed and deployed an MCP-exposed Documenso signing service, giving agents autonomous document-signing capability.
• Automated end-to-end tender submission through MCP tools, replacing a manual multi-step process for agents.

• Google ADK document pipeline in production
• MCP-exposed autonomous signing service
• End-to-end tender submission automation

Google ADKMCPTypeScriptNode.jsAI AgentsBackend Systems

• Engineered a fault-tolerant AI agent orchestration system using Inngest to manage document ingestion workflows, handling automated retries and fan-in/fan-out concurrency, eliminating manual failure intervention.
• Persisted ingested data into pgvector and Neo4j to support downstream RAG features.
• Containerized the full stack (backend services, Inngest server, and databases), enabling reproducible local development and smooth infrastructure migration.
• Implemented end-to-end with NestJS (backend) and React (frontend).

• Fault-tolerant Inngest orchestration
• Dual pgvector + Neo4j storage
• Full-stack containerization

InngestNestJSNeo4jpgvectorPostgreSQLDockerReactTypeScriptView repository

• Designed 2D and 3D route arrangements with stress calculations for heat distribution across 10+ UK sites.
• Identified operational hazards for contractors in construction and handover phases.
• Mentored an intern and colleagues on construction design workflows and structural CAD modeling.

• Stress calculations across 10+ UK sites
• Structural hazard mitigation
• Technical mentorship

Civil 3DsisKMRStress CalculationsCADSystems Engineering

• Conducted electromechanical systems engineering analysis for vertical transportation and elevator systems.
• Inspected installation tolerances, safety compliance standards, and mechanical sensor systems across commercial facilities.
• Collaborated with senior field engineers on preventative maintenance protocols and diagnostic workflows.

• Electromechanical systems analysis
• Safety and tolerance verification

Electromechanical SystemsSafety StandardsSensorsDiagnostics

Field of study · Computer Science & AI

• Distinction average (WAM 83).
• Relevant coursework in Computer Science, Software Engineering, and AI.
• Conducting research in GraphRAG memory management and architectural compliance for intelligent coding agents.

Field of study · Architecture and Engineering in IoT

• Specialisation in Architecture and Engineering in IoT.
• Key turning point sparking the transition from physical automotive engineering to computer science and applied AI.
• Studied distributed systems, networking protocols, embedded Linux, and sensor networks.

Field of study · Automotive & Mechanical Systems Engineering

• Comprehensive physical systems engineering curriculum: Mechanical Engineering, Electrical Engineering, and Project Management.
• Undergraduate thesis research on 6-DOF robotic probe tracking for medical ultrasonography training (published at IEEE TENCON 2023).