Building the Cloud Foundation for an AI Recruitment Platform

The Situation

TezHire is an AI-powered recruitment platform using automated screening and real-time candidate evaluations to streamline hiring. As interview volumes grew, the infrastructure underneath it needed to keep pace — automatically, reliably, and without a team of operators watching it overnight.

What Wasn’t Working

The original architecture leaned on managed virtual servers. As the platform scaled, three problems surfaced repeatedly:

• Manual OS patching ate engineering time that should have gone to features.
• Idle servers ran at full cost during off-peak hours.
• Configuration differences between dev, staging, and production caused deployment failures that were hard to trace and painful to fix.

The business needed a serverless foundation that could absorb traffic surges, integrate with AI APIs, and deploy new code without risk.

The Approach

We chose AWS CDK in TypeScript as the foundation. CDK lets you write infrastructure the same way you write application code: testable, modular, and reviewable in pull requests. The entire network — VPCs, databases, APIs, auth, CDN routing — became a codebase.

What Was Built

Network Layer

Identical Dev, Staging, and Prod environments declared in reusable TypeScript stack definitions. Secure, multi-AZ VPC layouts with Aurora Serverless databases isolated inside private subnets. CloudFront distribution rules for static web assets served directly from edge locations.

Compute & AI Integration

API Gateway routing to modular Lambda functions. AI API integrations to AWS Bedrock and Google Gemini for real-time candidate processing. Cognito user pools for OAuth-compliant authentication across multi-tenant sessions.

Delivery Pipeline

GitHub Actions pipelines for 5+ microservices — code linting, SonarQube quality gates, and automated rollbacks on failure. Every production deploy is reviewed, tested, and recoverable.

The Results

• 99.9% uptime — 10K+ monthly AI queries without a single service lockup.
• 40% faster releases — From multi-day deployment cycles to same-day production updates.
• Zero server overhead — No OS patches, no idle compute costs, no manual scaling events.

What I Took Away

Infrastructure as Code is not a best practice — it’s a forcing function. When your staging environment is defined in the same TypeScript codebase as production, “it worked on my machine” stops being a possibility. The discipline that CDK enforces pays back every time you ship.

Serverless compute isn’t just about cost — it’s about removing the class of problems that come with managing servers. When your database scales to zero during quiet hours and back up in milliseconds during traffic peaks, your team stops thinking about infrastructure capacity and starts thinking about product.