AI-Augmented Backend Engineer (Python/Django)

AI on the Hill; New Jersey; On-site; USD 100,000 - 150,000; Full time

Job summary

Hill Research is building a SaaS platform for clinical trial statistical programming and reporting, with AI powering roughly 70% of engineering execution.

We’re seeking an engineer who strengthens fundamentals—APIs, databases, reliability—and designs clean, maintainable backends. You’ll use Claude Code, Cursor, Copilot and related AI tools to move fast, while reviewing and improving AI-generated code.

Join a team focused on production-grade reliability and scalable, multi-tenant architectures.

Qualifications

• Experience building multi-tenant SaaS backends.
• Strong knowledge of APIs, databases, and reliability.
• Familiarity with AI-assisted development tools.
• Ability to review and improve AI-generated code.

Responsibilities

• Build multi-tenant SaaS backend systems.
• Develop workflow-heavy business logic.
• Ensure production-grade reliability and performance.
• Create AI-integrated backend services.

Skills

APIs & DBs

Backend design

AI tools (Claude Code/Cursor/Copilot)

Code review & debugging

Tools

PostgreSQL

Redis

AWS

Docker

Python

Django

Job description

About The Role

At Hill Research, we are building a SaaS platform for clinical trial statistical programming and reporting. But more importantly — we are building a company where AI powers ~70% of engineering execution.

About The Role

At Hill Research, we are building a SaaS platform for clinical trial statistical programming and reporting. But more importantly — we are building a company where AI powers ~70% of engineering execution.

That Means

• AI assists with code generation, test scaffolding, refactoring, documentation, and workflow automation
• Engineers focus on architecture, system design, production reliability, and judgment

We are not looking for someone who occasionally uses AI tools. We’re looking for an engineer who:

• Has strong fundamentals (APIs, databases, reliability, debugging)
• Designs clean, maintainable backend systems
• Uses tools like Claude Code / Cursor / Copilot to move faster
• Can review, debug, and improve AI-generated code with sound engineering judgment

Tech Stack

• Python
• Django 5.x
• Django Ninja
• Django Tenants (multi-tenant SaaS)
• PostgreSQL
• Redis
• AWS (S3, Lambda)
• Docker
• uv
• LLM / agent backend modules

What You’ll Be Building

• Multi-tenant SaaS backend systems
• Workflow-heavy business logic
• Production-grade reliability and performance
• AI-integrated backend services

AI-augmented engineering is our default workflow — but engineering fundamentals still matter.