Full Stack / Backend Engineer Intern – AI Deployment & Infrastructure

Qualifications

• Technical Foundation: Hands‑on coursework or projects in NLP/ML using PyTorch or TensorFlow
• Backend Experience: Strong skills in Python or Node.js, and familiarity with frameworks like FastAPI, Django, or Express
• API & Database Skills: Experience designing and maintaining REST APIs and working with relational databases (PostgreSQL or similar)
• Frontend Familiarity (Bonus): Exposure to React, Vue, or modern JS frameworks
• DevOps Know-How: Familiarity with Docker, container orchestration, and deploying cloud-native applications
• AI Product Interest: Passion for how AI capabilities are brought to life in production systems
• Startup Mindset: You're a self-starter who thrives in fast-paced, ambiguous environments and enjoys wearing multiple hats

Benefits

• Schedule: Flexible (20-40 hours/week)
• Duration: Summer 2025 (8–10 weeks, with potential to extend)
• Compensation: Unpaid (with potential for future paid role + equity)

Responsibilities

• AI-Driven Feature Development: Build and maintain backend and full-stack features where LLM agents and self-healing algorithms are deployed in real-time
• Infrastructure Design: Architect scalable systems that support low-latency inference, model pipelines, and secure data handling
• Full Stack Contributions: Collaborate on frontend/backend workflows to support a seamless testing experience across web, mobile, desktop, and APIs
• DevOps & Performance: Optimize system reliability, speed, and deployment workflows using Docker, cloud platforms, and CI/CD pipelines
• Cross-Functional Collaboration: Work closely with our AI/ML team to integrate models into production-ready applications
• Deep Learning Focus: Work with bleeding‑edge LLMs and self‑healing systems in a production environment

Full Description

About the Job

Location: Remote

Schedule: Flexible (20-40 hours/week)

Duration: Summer 2025 (8–10 weeks, with potential to extend)

Compensation: Unpaid (with potential for future paid role + equity)

Start Date: We are looking for candidates who can start as soon as possible

About Zof.ai

Zof.ai is reinventing software QA with AI‑driven, no‑code testing agents. We’re building the future of aut

onomous test generation, execution, and self‑healing—helping teams ship faster with fewer bugs.

What You’ll Do

• AI-Driven Feature Development: Build and maintain backend and full-stack features where LLM agents and self-healing algorithms are deployed in real-time.

• Infrastructure Design: Architect scalable systems that support low-latency inference, model pipelines, and secure data handling.

• Full Stack Contributions: Collaborate on frontend/backend workflows to support a seamless testing experience across web, mobile, desktop, and APIs.

• DevOps & Performance: Optimize system reliability, speed, and deployment workflows using Docker, cloud platforms, and CI/CD pipelines.

• Cross-Functional Collaboration: Work closely with our AI/ML team to integrate models into production-ready applications.

What You Have

• Technical Foundation: Hands‑on coursework or projects in NLP/ML using PyTorch or TensorFlow.

• Backend Experience: Strong skills in Python or Node.js, and familiarity with frameworks like FastAPI, Django, or Express.

• API & Database Skills: Experience designing and maintaining REST APIs and working with relational databases (PostgreSQL or similar).

• Frontend Familiarity (Bonus): Exposure to React, Vue, or modern JS frameworks.

• DevOps Know-How: Familiarity with Docker, container orchestration, and deploying cloud-native applications.

• AI Product Interest: Passion for how AI capabilities are brought to life in production systems.

• Startup Mindset: You're a self-starter who thrives in fast-paced, ambiguous environments and enjoys wearing multiple hats.

Why Zof.ai?

• Early Impact: Shape core AI features alongside our founding engineer.

• Rapid Growth: Join a nimble team driving real‑world adoption across web, mobile, desktop, and API testing.

• Deep Learning Focus: Work with bleeding‑edge LLMs and self‑healing systems in a production environment.

Ready to redefine software testing? Apply today! 🚀