Backend Engineer → Cloud / DevOps Focus

• Build backend systems using Go (Gin) and Node.js (Express)
• Design APIs, data models, and service boundaries
• Operate containerized workloads and self-managed infrastructure
• Work with PostgreSQL, MongoDB, Redis, and observability stacks

Backend Engineering Intern

• Contributed to Identity & Access Management (IAM) systems
• Built internal SDKs for authentication and service integration
• Developed AI agent-based automation for internal workflows
• Wrote integration tests and proof-tested libraries to ensure reliability
• Focus: security boundaries, system design, and interoperability

Backend system for international Model United Nations events

• Handles ~1000 users with traffic spikes during registration windows
• Ensured data consistency under concurrent writes (PostgreSQL transactions)
• Implemented idempotent retries for safe failure recovery
• Applied timeouts and IP-based rate limiting at middleware level
• Integrated structured logging for observability

Focus: reliability under burst traffic, failure handling, consistency

Personal infrastructure for running and operating services

• Provisioned with Terraform, configured via Ansible
• Observability stack: Prometheus · Grafana · Loki · Node Exporter
• Secured services using Cloudflare Zero Trust
• Designed around monitoring-first and controlled access principles

Focus: infrastructure automation, observability, secure exposure

Online testing system for timed, multi-section evaluations

• Designed microservice architecture with gRPC communication
• Planned Redis-based session/state management
• Focused on isolating test execution under concurrent usage

Architecture-focused; implementation is partial

Exploring GitOps workflows for research data platforms

• Kubernetes-based deployment model
• Git-driven infrastructure and environment control
• Exploring OpenTelemetry for tracing and observability

• Structured logging for debuggability
• Moving toward OpenTelemetry (tracing + metrics)
• Idempotent operations and retry-safe design
• Atomic database transactions for consistency
• Integration testing for reliability before release

• Kubernetes in constrained environments
• Infrastructure as Code (Terraform)
• CI/CD and deployment automation
• Designing systems that remain stable under real-world conditions

“Continuous improvement is better than delayed perfection.”