Junior AI Engineer

Magna International•Troy, MI

3d•Hybrid

About The Position

The Junior AI Engineer will help design, develop, integrate, and support artificial intelligence solutions that improve business processes and employee productivity. Working alongside experienced engineers and IT teams, this early-career engineer will build process-improvement applications using generative AI, large language models, machine learning, APIs, automation, software applications, and cloud services. The role offers hands-on experience delivering secure, responsible, enterprise-scale process-improvement software. The position is in the Information Technology department and is based in the Michigan and Toronto, Canada area, with hybrid or on-site work as applicable. No relocation or sponsorship is offered.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Technology, a related discipline, or equivalent practical experience.
0–2 years of professional software-development, data, automation, or AI experience.
Programming experience with Python.
Understanding of software-development fundamentals, including APIs, data structures, object-oriented programming, source control/Git, testing, and debugging.
Basic understanding of machine learning, generative AI, and large language models.
Familiarity with JSON, REST APIs, SQL, and common data formats.
Strong analytical and problem-solving skills.
Strong written and verbal communication skills.
Ability and willingness to learn new technologies quickly.
Curiosity and strong interest in emerging technologies and experimentation.
Ability to build maintainable solutions beyond demonstrations.
Ability to break complex business problems into manageable technical components.
Awareness that AI solutions require attention to security, privacy, bias, accuracy, and human oversight.
Ability to work effectively across technical and business teams.
Ability to explain technical concepts clearly to technical and nontechnical audiences.
Comfort working in a rapidly evolving technology environment.

Nice To Haves

Experience or academic/project exposure to web development.
Experience or academic/project exposure to .NET development.
Experience or academic/project exposure to CAD and FEA software integration.
Experience or academic/project exposure to AI agents and agentic workflows.
Experience or academic/project exposure to Microsoft Copilot Studio.
Experience or academic/project exposure to prompt engineering.
Experience or academic/project exposure to Retrieval-Augmented Generation (RAG).
Experience or academic/project exposure to vector databases and semantic/vector search.
Experience or academic/project exposure to Semantic Kernel or similar AI orchestration frameworks.
Experience or academic/project exposure to machine-learning frameworks such as PyTorch or TensorFlow.
Experience or academic/project exposure to Docker and containerized applications.
Experience or academic/project exposure to GitHub.
Experience or academic/project exposure to CI/CD pipelines.
Experience or academic/project exposure to SQL and NoSQL databases.
Experience or academic/project exposure to enterprise identity and security concepts.
Experience or academic/project exposure to data analytics and visualization.

Responsibilities

Assist with the design and development of AI-enabled applications and automation solutions.
Develop applications that integrate with LLMs, traditional machine-learning models, and generative AI services.
Build and maintain prompts, structured outputs, tool/function integrations, and AI workflows.
Assist with implementing Retrieval-Augmented Generation (RAG) solutions using enterprise data sources.
Evaluate model responses for accuracy, relevance, reliability, and overall user experience.
Participate in prototyping and proof-of-concept development for new AI use cases.
Develop and maintain applications and services using Python, .NET, and other supported development languages.
Build and consume REST APIs and integrate AI capabilities with existing enterprise applications.
Work with structured and unstructured data from databases, documents, APIs, and business systems.
Use source control and modern software-development practices, including Git, CI/CD, testing, and code reviews.
Assist with troubleshooting, debugging, performance optimization, and production support.
Follow organizational standards for Responsible AI, security, privacy, and data governance.
Assist with implementing logging, monitoring, evaluation, and feedback mechanisms for applications.
Ensure sensitive and confidential organizational information is handled appropriately.
Integrate applications to function with existing CAD, FEA, and PDM software.
Translate business requirements into technical prototypes and solutions with guidance from senior team members.
Stay informed about developments in generative AI, machine learning, software engineering, and CAD/FEA automation.
Share findings, demonstrations, documentation, and lessons learned with the broader technology organization.