Back End Developer - AI Agentic Infrastructure

Backend Developer Intern — Agentic AI Infrastructure

Technology Stack: Python, FastAPI, Async Python, LLMs, Agent Orchestration, Databases

About the Role

We are looking for a Backend Developer Intern to help build the infrastructure behind our production Agentic AI systems.

This is not a sandbox or tutorial-based internship. You will work on real systems that sit underneath AI agents — APIs, orchestration, state management, tool execution, retries, streaming, observability, and failure recovery.

Building backends for AI agents presents different challenges from traditional CRUD applications. LLM calls can be slow, nondeterministic, and expensive. The interesting engineering work is often everything surrounding the model: handling timeouts without duplicating side effects, streaming partial responses correctly, tracking state across multi-step agent runs, recovering from failures, and designing APIs that remain reliable when an external model takes 20 seconds instead of 200 milliseconds.

We are looking for someone who enjoys understanding why a system works, not simply getting it to run.

What You'll Do

• Design and build backend services using Python and FastAPI
• Build APIs that power AI agents and LLM-based applications
• Develop asynchronous workflows for long-running LLM and external API calls
• Build orchestration around agent execution, including retries, timeouts, idempotency, and state management
• Manage state across multi-step agent and tool-calling workflows
• Implement streaming responses for long-running AI operations
• Work with relational and/or NoSQL databases for application data, agent state, and execution history
• Design schemas, queries, migrations, and indexes for real workloads
• Implement rate limiting, particularly around expensive LLM/API operations
• Build logging and observability for agent runs and failures
• Write automated tests covering both successful and failure scenarios
• Debug slow queries, race conditions, flaky integrations, and external API failures
• Follow secure development practices, including proper secret and credential management
• Collaborate asynchronously with a small engineering team through clear documentation and written updates

What We're Looking For

• Currently pursuing or recently completed a degree in Computer Science, IT, Engineering, or a related field
• Strong fundamentals in Python
• Hands-on experience with FastAPI, or experience with Flask/Django and an interest in FastAPI
• Understanding of async/await and asynchronous Python
• Understanding of REST APIs and HTTP concepts
• Basic understanding of database design and SQL and/or NoSQL databases
• Comfortable using Git and standard development workflows
• At least one original project on GitHub that you personally built and can explain
• Strong interest in LLMs, AI agents, and production AI infrastructure

Prior professional experience with Agentic AI is not required.

Strong Signals

The following are not requirements, but they will help your application stand out:

• Experience integrating OpenAI, Anthropic, Gemini, or another LLM API
• Experience building tool-calling or multi-step AI workflows
• Experience with LangGraph, CrewAI, or similar orchestration frameworks
• Experience writing automated tests for personal or academic projects
• Understanding of concurrency, retries, rate limiting, and failure recovery
• Exposure to streaming APIs or WebSockets
• Experience with PostgreSQL, Redis, vector databases, or similar technologies
• Experience with Docker and CI/CD
• Experience deploying applications to AWS, GCP, Azure, Render, Railway, or similar platforms
• Awareness of basic application security and secret management

What You'll Get

• Hands-on experience building production Agentic AI infrastructure
• Real engineering ownership from day one
• Opportunity to ship features used in production
• Direct mentorship and code reviews from the founding team
• Experience solving real-world backend reliability and scalability problems
• Exposure to modern LLM and AI-agent architecture
• Remote-first and async-friendly working environment
• Internship completion certificate
• Strong recommendation based on performance
• Opportunity to convert to a full-time engineering role based on performance and business requirements

How to Apply

Please submit:

1. Your resume

2. Your GitHub profile

3. A link to one project you personally built

4. A short explanation of the hardest technical problem you encountered while building that project and how you solved it

We review applications by looking at the work you have actually built, not only your resume.

A small, original project that you understand deeply is more valuable to us than a long list of tutorial projects.