Full Stack Development: Build, deploy, and maintain highly scalable backend services using Node.js in an AWS Lambda architecture, alongside dynamic front-end SPAs using ReactJS.
AI-Accelerated Engineering: Utilize AI agents and LLMs to accelerate coding, debugging, and testing phases while maintaining strict quality control over all AI-generated outputs.
Workflow & Architecture: Design and implement robust event-driven and asynchronous workflows for scalable data processing.
System Integration: Develop and integrate core APIs and internal services, troubleshooting full-stack production issues from the user interface down to the database.
Code Quality & Review: Write comprehensive unit and integration tests, participate in rigorous code reviews, and champion engineering excellence.
Cross-Functional Collaboration: Partner closely with Product, DevOps, and Security teams to architect and ship solutions that are both secure and highly resilient.
Required Qualifications Core Engineering & Cloud:
Node.js Expertise: Strong hands-on experience building production-grade backend services using Node.js (asynchronous patterns, advanced error handling, performance optimization).
Front-End Proficiency: Extensive experience developing Single Page Applications (SPAs) using ReactJS, including seamless integration and deployment within an AWS environment.
AWS Serverless Architecture: Proven experience designing and deploying services using AWS Lambda (environment configuration, deployment strategies, and event sources).
API Management: Working knowledge of AWS API Gateway, including REST/HTTP endpoint creation, custom authorizers, and backend integrations.
Data Warehousing: Exposure to Amazon Redshift, including an understanding of core data warehousing concepts, basic querying, and building data pipelines.
Infrastructure & Automation: Familiarity with Infrastructure as Code (IaC) principles using Terraform, as well as pipeline automation via GitHub Actions.
System Debugging: Exceptional ability to debug distributed systems. Proficiency in using logs, metrics, and structured troubleshooting methodologies.
AI & Modern Workflows:
AI-Assisted Development: Proven experience using AI Agents and coding assistants to accelerate the software development lifecycle.
Prompt Engineering & Technical Discernment: Strong prompt engineering skills with the deep technical savviness required to effectively review, test, accept, refactor, or discard AI-generated code.
Version Control: Solid familiarity with Git-based workflows and CI/CD best practices