AI Engineer Intern

About the role

About initializ.ai

initializ.ai is an enterprise AI platform for building, governing, and operating AI agents in production. Our products — AIP (multi-cloud agent operations with policies, guardrails, and auditing) and Forge (which compiles agent definitions into governed, deployable units) — help enterprise engineering teams run agents safely against real business systems. We work on hard problems at the intersection of applied machine learning, distributed systems, and security.

Position Summary

The AI Engineer Intern will work alongside our engineering team on production components of the initializ platform. This is a hands-on engineering role: the intern will write code that ships, participate in design reviews, and own scoped deliverables under a senior engineer's mentorship.

Responsibilities

Build and improve components of our retrieval-augmented generation (RAG) service, including hybrid retrieval (BM25 + dense vectors with reciprocal rank fusion), query understanding, and relevance scoring

Develop and extend evaluation harnesses for agent and retrieval quality — golden datasets, regression suites, offline metrics

Implement MCP (Model Context Protocol) tool integrations connecting agents to external enterprise systems

Contribute to FastAPI microservices and supporting Python data pipelines for document ingestion, chunking, and embedding generation

Add instrumentation, logging, and telemetry to agent execution paths; analyze results and present findings

Participate in code review, sprint planning, standups, retrospectives, and design spike sessions

Required Qualifications

Currently enrolled in a Bachelor’s or Master’s program in Computer Science, Computer Systems Engineering, Artificial Intelligence, Data Science, or a closely related field

Proficiency in Python; familiarity with Git and collaborative development workflows

Working understanding of probability, linear algebra, and vector representations as applied to embeddings and similarity search

Ability to read technical documentation and reason about system design tradeoffs

Preferred Qualifications

Exposure to LLM application frameworks, vector databases, or transformer-based models

Familiarity with REST API design, containers (Docker), or Kubernetes

Coursework or projects in distributed systems, databases, or cloud computing

TypeScript / React experience for platform UI contributions

Learning Outcomes and Mentorship

The intern is assigned a designated supervisor/mentor who provides structured feedback through weekly 1:1s, pull request review, sprint ceremonies, and written mid-term and end-of-term evaluations. By the end of the term, the intern will have:

Shipped production code to a live enterprise AI platform

Learned to evaluate ML system quality empirically rather than anecdotally

Gained experience with the engineering practices of a production software team — version control at scale, code review, CI/CD, incident awareness, and agile delivery

How to Apply

Send a resume and a short note describing a project you have built to careers@initializ.ai

initializ is an equal opportunity employer.