Hamza Hassan

• Built and shipped a full-stack AI-powered resume and job application platform solo, acquiring organic traction and winning Product of the Day on Microlaunch.

• Designed and implemented the end-to-end AI pipeline for job-specific resume tailoring, cover letter generation, and ATS optimization using LLMs.

• Built a Chrome extension enabling one-click job description parsing and instant resume matching directly from job listing pages.

• Architected and operated the entire cloud infrastructure on AWS using Pulumi, including serverless functions, RDS, and CDN layers.

• Owned the entire product workflow solo, from Notion specs and SVG low-fidelity designs through to AWS infrastructure, production deployment, and growth tracking via Google Analytics.

• Applied extensive and methodical prompt engineering with Cursor to systematize AI-assisted development across the full stack, shipping at the pace of a 3-4 person team.

• Led a special project as Expert Product Manager, coordinating 40+ software engineers to design, build, and deliver 35+ Model Context Protocol (MCP) servers for a top AI research lab.
• Automated 90% of the end-to-end delivery workflow, from SME spec creation to MCP trajectory generation, cutting manual overhead and significantly accelerating team output.
• Calibrated rubrics and reinforcement learning environments, ensuring consistent evaluation standards across a large distributed engineering team.
• Trained an RL model on 170+ open-source repositories across TypeScript, Go, and Python, improving model reasoning, code completion accuracy, and multi-language adaptability.
• Built and deployed multi-agent systems with n8n integration, automating complex cross-functional workflows and improving experiment reproducibility at scale.

• Led migration from monolithic to microservices architecture, decomposing a legacy Ruby on Rails app into independent NestJS and Serverless services, improving deployment agility, fault isolation, and horizontal scaling.
• Designed an event-driven architecture using AWS EventBridge and SQS, streamlining data synchronization between microservices and ensuring real-time data consistency.
• Optimized backend data pipelines by restructuring database queries and leveraging PostgreSQL indexing, achieving a 60% decrease in query response times under high-load conditions.
• Designed end-to-end cloud architecture with GitHub Actions CI/CD, Docker, and Kubernetes on EKS, ensuring zero-downtime deployments across core applications.
• Built test automation suites with Jest and RSpec, reducing production bugs by 30% and improving overall release stability.
• Enhanced real-time data performance with Redis caching and PostgreSQL Views, speeding up financial transaction processing.

• Developed end-to-end features including time-tracking, interviewing, and KPI history for a team management platform using Ruby on Rails, PostgreSQL, and React.
• Built a scalable Node.js server with PostgreSQL and RabbitMQ for background job processing, improving response times under high-traffic conditions.
• Enforced code quality with Prettier, ESLint, and Husky, and established CI/CD pipelines on GitLab, improving development speed by 25%.

• Built a scalable GraphQL e-commerce platform on Node.js with React frontend and MSSQL, optimizing data retrieval for over 5 million product parts.
• Enhanced search performance by integrating Elasticsearch and Redis caching, reducing response times for high-volume product queries.
• Integrated third-party payment systems including Stripe and PayPal, streamlining transaction reliability.
• Developed reusable styled components with MaterialUI, standardizing design across the application.

A platform-agnostic cloud infrastructure components library for modern applications. Built with TypeScript and Pulumi, Infra Foundry provides reusable, composable infrastructure components that work across AWS, Cloudflare, and Vercel.

Built and engineered an end-to-end, 10-stage GTM engine for an AI-evaluation startup using TypeScript and GitHub Actions. Designed as an idempotent, Notion-backed state machine, the pipeline processes YC prospects via a provider-agnostic Claude client (Anthropic and AWS Bedrock via secure OIDC) with automatic model fallback and an automated, fail-closed IMAP reply-sweeper. To drive growth, I transformed pipeline artifacts into AI-generated evaluation rubrics that double as cold-outreach lead magnets, turning backend infrastructure into a high-leverage product-led growth loop.