Aquila — AI Data Production Platform
Aquila is an AI-powered platform for managing and evaluating software engineering and AI data production workflows. It combines automated task assessment, secure code execution, deployment automation, project management, and workforce operations into a single system—enabling teams to build, test, review, and validate work efficiently at scale.
My Key Contributions
AI-Powered Task Evaluation
Built systems that use AI to automatically review completed tasks, verify requirements, identify issues, and provide feedback before human review—improving both quality and review efficiency. Pluggable AI provider adapters (registry pattern) drive live LLM calls with cost tracking and response comparison.
Secure Sandbox Execution
Developed infrastructure that safely runs submitted code in isolated environments via AWS CodeBuild—dynamic buildspec rendering, automated functionality testing, output validation, and AI-based assessment of results, with reports persisted to S3.
Automated Deployment & Preview Generation
Built pipelines that spin up ephemeral EC2 preview environments running docker compose per task branch—auto-resolving AMIs via SSM, pulling secrets from Secrets Manager, with TTL-based teardown and drift reconciliation so reviewers can instantly test completed work.
Inside the Platform
Secure AI Data Production Environment
A highly secure environment with an integrated coding IDE where contributors build datasets end-to-end (0 → 1) under strict, no-copy-paste workflows.
Workforce Management System
More than a coding environment—Aquila integrates personnel management, project management, engineering workflows, and evaluation systems into one operational backbone.
Hiring & Training Pipeline
Every developer goes through a one-week pre-hire training phase, evaluated by the Key Engineering team, with hiring decisions based on measured performance.
Quality & Evaluation Infrastructure
Supports task creation, task review, dataset validation, contributor evaluation, and engineering quality control to keep AI training data consistent and rigorous.
Tech Stack
A FastAPI backend built on clean architecture, deployed on AWS with deep automation, AI evaluation, and production-grade observability.
Core & API
Data
Cloud & Infra
AI
Auth & Security
Async & Jobs
Observability
Integrations
Are you interested?
Let's work together on your project.