
About Me
As a software engineer, I leverage a versatile skill set that spans from high-level web applications to low-level systems programming. My foundation in full-stack development with React, Next.js, and TypeScript is complemented by deep experience in Python for machine learning and C++ for real-time data processing. This combination allows me to build robust, end-to-end solutions tailored for performance and reliability.
I am driven by the challenge of creating software for high-stakes environments, particularly in the defence and simulation sectors, where clarity and precision are paramount. I thrive on engineering that solves concrete problems and am constantly expanding my toolkit to build more efficient and resilient systems.
Case Studies
A selection of engineering challenges I have successfully navigated. Each case study breaks down my process for analysing complex problems, architecting robust solutions, and delivering measurable improvements in automation and efficiency.
Client Onboarding Portal Automation
Challenge
Manual client onboarding process requiring 1-2 hours per client via phone and email, for over 50 new clients monthly.
Analysis
Key Findings:
- Multiple phone calls and emails required per client
- Information scattered across calls, emails, and manual forms
- Clients frustrated by interruptions during business hours
- Staff spending 120+ hours monthly on repetitive data collection
- High error rate due to manual transcription and missed details
Decision
Implementation
Results
Key Lessons:
- Overcoming API documentation gaps requires patience and experimentation.
- Continuous improvement should be driven by direct feedback from both clients and internal users.
- Robust security measures are non-negotiable for client-facing portals.
- Webhook-based automation is key to enabling seamless, real-time workflow integration.
Automated Hourly Reporting System
Challenge
Daily requirement to submit hourly, strictly formatted compliance reports, consuming over 40 minutes of development time each day.
Analysis
Key Findings:
- Eight hourly reports plus end-of-day summary required daily
- Strict formatting template with specific spacing and line breaks
- Manual time calculations and overtime justification logic
- Context switching disrupted complex problem-solving sessions
- High risk of formatting errors affecting compliance
- Significant mental overhead required to manually track and meet reporting deadlines.
Decision
Implementation
Results
Key Lessons:
- Targeted automation can preserve deep work focus, significantly boosting technical productivity.
- AI integration is highly effective for transforming unstructured user input into structured, professional output.
- Well-designed automation can satisfy stringent compliance requirements while reducing cognitive load.
- Demonstrating improved consistency and reliability can lead to positive management recognition.
My Projects
Let's connect and explore opportunities
I'm actively seeking new opportunities and open to discussing roles, projects, or collaborations. Feel free to reach out!