AI Intern

Avaloka.ai; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

Avaloka.ai is seeking a talented engineer to join the data science workflow team. You will help build multi-agent workflows and support backend infrastructure in a production environment.

You will construct workflows with LangGraph, create Python-based APIs using FastAPI, and deploy solutions across AWS, Azure, or GCP while improving observability and performance.

Qualifications

• Solid proficiency in Python across multiple use cases.
• Hands-on experience developing APIs.
• Working knowledge of large language models, including prompt design, tool calling patterns, and retrieval-augmented generation
• Ability to think through system design and performance considerations in distributed environments

Responsibilities

• Construct multi-agent workflows using LangGraph with routing logic, state management, memory handling, tool integration, and retry mechanisms
• Create backend APIs and services with Python and FastAPI to power agent systems
• Implement testing strategies, set up tracing for observability, and deploy solutions across AWS, Azure, or GCP
• Debug and optimize agent behavior as workflows move toward production

Skills

Python

APIs

LLMs knowledge

Distributed systems design

Tools

LangGraph

FastAPI

AWS

Azure

GCP

Job description

Batch: 2026/2027/2028.

About the role:

• Avaloka brings together AI agents to tackle data science challenges
• You'll join the engineering team building multi-agent workflows and supporting backend infrastructure

What you'll work on:

• Construct multi-agent workflows using LangGraph with routing logic, state management, memory handling, tool integration, and retry mechanisms
• Create backend APIs and services with Python and FastAPI to power agent systems
• Implement testing strategies, set up tracing for observability, and deploy solutions across AWS, Azure, or GCP
• Debug and optimize agent behavior as workflows move toward production

What we're looking for:

• Solid proficiency in Python across multiple use cases
• Hands-on experience developing APIs
• Working knowledge of large language models, including prompt design, tool calling patterns, and retrieval-augmented generation
• Ability to think through system design and performance considerations in distributed environments