Building reliable, serverless systems on AWS using Go, TypeScript, and modern DevOps practices.
Backend & DevOps engineer specializing in AWS serverless architectures, automation, and observability.
I design and build end-to-end systems using Go and TypeScript — from event pipelines and analytics to CI/CD and self-hosted environments.
Passionate about simplifying operations and turning complex workflows into scalable, maintainable solutions.
AWS Services Deployed
Serverless Workflows Built
Production CI/CD Pipelines
Major System Migrations
Infrastructure as Code (IaC)
Self-hosted Apps Deployed
React, Go, MongoDB
A full-stack calendar form expense tracker powered by Go and React, backed by DynamoDB, and privately deployed on my self-hosted homelab. Accessible only through my Tailnet for secure, VPN-based access.
Lamda → Step Function → Firehose → S3 → Glue → Athena → DynamoDB
A serverless analytics architecture built with AWS Lambda, Step Functions, and Firehose. Seamlessly transforming and analyzing event data through S3, and Glue powering low-latency access to aggregated insights.
API Gateway + Lambda authorizer managed in AWS SAM
A secure API Gateway setup with custom Lambda authorizers providing role-based access per client using unique API keys — all managed through AWS SAM for scalable, infrastructure-as-code deployment.
Lambda that triggers Athena jobs via Event bridge, stores results in DynamoDB
A fully automated analytics function that runs Athena queries on scheduled intervals via EventBridge, aggregates results, and stores them in DynamoDB. All serverless, scalable, and cost-efficient.
Jenkins Pipeline → Github Actions
Migrated legacy Jenkins pipelines to GitHub Actions. Achieving cleaner, faster, and fully version-controlled CI/CD with reusable workflows, automated testing, and environment-specific deployments.
From Ruby on Rails + PostgreSQL to React + Go + AWS SAM Microservices
Migrated legacy Jenkins pipelines to GitHub Actions. Achieving cleaner, faster, and fully version-controlled CI/CD with reusable workflows, automated testing, and environment-specific deployments.
Problem: As the product scaled, enabling or disabling experimental features across mobile and web clients required code redeployments.
This slowed down release velocity and increased the risk of introducing regressions when toggling new features.
Solution: Designed and implemented a centralized feature flag management system powered by AWS AppConfig, allowing controlled feature rollouts using a JSON configuration file.
The backend (Go microservices) retrieves the latest AppConfig configurations via the AWS SDK and caches them in memory for fast evaluation.
Frontend (React) and mobile clients consume the same configuration from an exposed API endpoint, ensuring synchronized feature behavior across platforms — without redeployments.
Problem: As the number of client integrations increased, access control became difficult to manage and audit.
The existing authentication layer used static shared tokens, which lacked fine-grained permissions, revocation control, and per-client monitoring.
This made it challenging to enforce secure, scalable access across multiple APIs.
Solution: Designed and implemented a role-based access control (RBAC) system powered by API Gateway and custom Lambda authorizers, fully managed through AWS SAM.
Each client is issued a unique API key linked to specific roles and permissions.
When a request is made, the Lambda authorizer validates the API key, looks up the associated permissions, and injects authorization context into the request before it reaches the backend services.
Interested in hiring or collaborating? I usually respond within a day. Share a short description of the role or project and links to relevant repos.