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# Junior AI Engineer

- **Company:** CGI Technologies and Solutions, Inc.
- **Location:** Salt Lake City, UT, United States
- **Experience:** Starter
- **Salary:** $70,800.0
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Cloud Engineering, Code Review, Computer Programming, Databases, Continuous Integration, Software Design Patterns, Python (Programming Language), Machine Learning, Standard Sql, Software Engineering, Web Application Frameworks, Google Cloud, Enterprise Software Applications, Chatbots, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Fastapi, Event Driven Architecture, Containerization, Kubernetes, Information Technology, Machine Learning Operations, Restful APIs, Automation Anywhere, Serverless Computing, Docker, Microservices
- **Published:** August 9, 2026
- **Apply:** https://www.juju.com/job/00000000gm6sbh

## About the Role

* Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related technical field, or equivalent practical experience

 * Up to 2 years of professional, internship, academic, or project-based experience in software engineering, AI, or machine learning development

 * Strong programming skills in Python and experience working with SQL

 * Understanding of machine learning fundamentals and Generative AI concepts

 * Hands-on experience working with Large Language Models (LLMs), including prompt engineering techniques

 * Experience building or working with Retrieval-Augmented Generation (RAG) architectures and vector databases

 * Familiarity with LangChain, LangGraph, or similar AI orchestration frameworks

 * Familiarity with AI agents, agentic workflows, and common agent design patterns

 * Experience working with or developing integrations using Model Context Protocol (MCP)

 * Familiarity with AI configuration and instruction files, such as `AGENTS.md`, `SKILL.md`, or similar artifacts used to define AI system behavior and capabilities

 * Understanding of REST APIs and microservices architecture

 * Familiarity with Docker and modern CI/CD practices

 * Strong analytical, problem-solving, collaboration, and communication skills

 * Curiosity, adaptability, and enthusiasm for learning and applying emerging AI technologies

Preferred Qualifications

Experience with one or more of the following is a plus:

 * MLOps tools, workflows, and deployment practices

 * Kubernetes and container orchestration

 * FastAPI or similar Python web frameworks

 * Cloud platforms such as Microsoft Azure, AWS, or Google Cloud

 * Serverless and event-driven architectures

 * High-availability, scalability, and autoscaling concepts

 * AI evaluation frameworks, model benchmarking, and quality measurement

 * AI security, governance, and responsible AI practices, + Agentic RAG

 + Artificial Intelligence

## Description

As a Junior AI Engineer, you'll collaborate with experienced engineers, architects, and business teams to design, build, and deploy AI-powered solutions that address real business needs.

Your responsibilities will include:

 * Design and develop AI-powered product features using Generative AI, machine learning, and Large Language Models (LLMs)

 * Build intelligent applications using Retrieval-Augmented Generation (RAG), embeddings, and vector database technologies

 * Develop conversational AI experiences, AI agents, and agent-based workflows

 * Build scalable REST APIs and FastAPI microservices to integrate and serve AI capabilities

 * Develop and maintain AI workflows using LangChain, LangGraph, and other modern agentic frameworks

 * Work with Model Context Protocol (MCP) servers and related tools to integrate AI applications with enterprise systems and data sources

 * Containerize applications using Docker and support deployment in Kubernetes environments

 * Contribute to cloud-native AI solutions designed for security, scalability, reliability, and maintainability

 * Collaborate with product managers, software engineers, architects, and business stakeholders to deliver innovative AI capabilities

 * Participate in code reviews, testing, troubleshooting, documentation, and continuous improvement initiatives

 * Stay current with the rapidly evolving AI ecosystem and help evaluate emerging models, frameworks, tools, and development practices


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