Selected backend projects where architecture decisions translated into measurable product impact.

Context

The platform needed AI-assisted tutoring while keeping student data private and maintaining stable performance under semester-level traffic spikes.

Key contributions

• Built Moodle plugin integrations with an API layer for local LLM orchestration.
• Implemented Redis-backed cache strategy for repeated tutor and recommendation flows.
• Introduced safer rollout patterns and monitoring for feature reliability.

Impact

• Reduced database load by ~40% on heavy query paths.
• Improved perceived response time for AI tutor interactions.
• Enabled privacy-conscious deployment by running models on internal infrastructure.

Context

The product required near real-time food recognition with stable processing throughput and consistent releases across multiple environments.

Key contributions

• Developed event-driven Golang services for image processing and metadata workflows.
• Integrated vector search using Qdrant to improve similarity matching quality.
• Standardized containerized deployment with Kubernetes-first operational patterns.

Impact

• Improved release confidence through repeatable CI/CD and environment parity.
• Scaled processing capacity with clearer service isolation and queue-driven execution.
• Reduced production incidents by tightening contracts between backend components.

Context

Growing LMS adoption created API bottlenecks and operational friction during peak usage periods, requiring a structured reliability push.

Key contributions

• Refactored high-traffic endpoints and optimized SQL/query plans for critical paths.
• Introduced performance baselines and observability dashboards for release gates.
• Codified incident learnings into repeatable runbooks and delivery checklists.

Impact

• Improved key API response times by approximately 40%.
• Raised deployment stability with clearer quality gates and rollback readiness.
• Reduced firefighting by increasing visibility into latency and failure trends.