Applied AI Engineer Intern

About Aira Technologies

Aira Technologies is a Silicon Valley start-up focused on automating telecom operations using cutting-edge AI and GenAI technologies. Founded by Qualcomm and Intel veterans. Backed by AT&T Ventures, Intel Capital, In-Q-Tel, NeoTribe, Acrew, and more.

Naavik™, our flagship AI-native platform, is built to be the autonomous driver for network operations. Visit aira‑technology.com.

Role Overview

We are seeking Applied AI Engineer Interns to help design and build intelligent, production-ready AI systems within our product stack. You will work on agentic systems: LLMs coordinated through tools, multi-step workflows, and retrieval over large bodies of structured domain data, all running inside real production services. You will collaborate closely with engineers to prototype, rigorously validate, and deploy AI components that directly impact business outcomes.

Key Responsibilities

• Build and extend multi-step agent workflows: define tools and drive tool-calling loops
• Build and tune retrieval components over large structured and semi-structured datasets
• Build evaluation harnesses: curate golden datasets, define accuracy and task-success metrics
• Develop async Python services for production-quality real time streaming
• Instrument agent runs (latency, token usage, tool-call traces) and fix weak links
• Maintain high engg. standards through code reviews, automated testing, and documentation
• Bring emerging research in LLMs, agentic architectures, and applied ML into the product

Required Qualifications

• Currently pursuing a Bachelor’s, Master’s, or PhD in CS, EE, AI, Data Science, or a related field.
• Strong Python skills, including asynchronous programming and type hints
• Understanding of embeddings, vector search, and RAG pipelines.
• Hands-on with prompting, context management, tool calling, and streaming LLM responses
• Agent systems (planning, tool use, HITL, multi-agent), ideally with LangGraph, AutoGen, or similar
• Hands-on experience in a modern service framework such as FastAPI or Flask.
• Comfortable writing automated tests and debugging distributed, async systems
• Fluent with Git and Docker; sandboxed code execution and secure coding is a plus
• Self-driven, curious, and comfortable working in a fast-paced environment.