AI Engineer

Vertiv•Westerville, OH

4h•Onsite

About The Position

The AI Engineer will design, build, and operationalize full stack AI applications that power Vertiv’s Enterprise AI Platform and other AI initiatives; and support the development and deployment of AI services and applications under guidance, contributing to components of retrieval pipelines and integrations with enterprise systems. This role focuses on developing foundational AI solutions while learning enterprise standards, governance, and scalability practices. This position will be based onsite at Vertiv's Westerville, OH - HQ location.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, or equivalent practical experience.
0–2+ years of professional or internship experience in software development.
Exposure to GenAI or LLM-based applications through coursework, projects, or early professional experience.
Strong experience with Python and SQL; experience building APIs and data driven services.
Foundational knowledge of LLMs, prompt engineering, or related concepts.
Familiarity with cloud environments (AWS or similar) and basic deployment concepts.
Ability to contribute to technical solutions and collaborate with team members to meet business requirements.

Nice To Haves

Experience with Snowflake for analytics, data access, or ML adjacent workloads.
Experience building internal AI tools or lightweight web apps for business users.
Basic familiarity with AI workflows or frameworks is a plus.
Exposure to AI evaluation or monitoring concepts is a plus.

Responsibilities

Assist in developing components of AI applications across the stack, including web interfaces, backend APIs, and AI services deployed on AWS.
Support the development and maintenance of Retrieval Augmented Generation (RAG) pipelines, including document ingestion, embeddings, and retrieval processes.
Develop and enhance AI services and APIs following established standards and guidance.
Contribute to implementation of AI capabilities and assist with enabling usage by application teams and business users.
Integrate approved large language models through existing APIs with guidance from senior team members.
Assist with connecting AI applications to enterprise data sources such as Snowflake under defined patterns.
Consume and work with secure APIs and follow established governance, security, and compliance practices.
Contribute to CI/CD pipelines and deployment processes using established tools and frameworks.
Support monitoring and evaluation of AI solutions using existing observability tools and metrics.
Collaborate with team members and stakeholders to support delivery of AI use cases.
Document work, processes, and technical components following team standards.