DevOps Engineer I

Florida Polytechnic University•JD Alexander Florida Polytechnic Main Campus, FL

2d•Onsite

About The Position

As a collaborative member of the DevOps Team in Information Technology Services, the DevOps Engineer I contributes to Florida Poly’s initiative to build an AI-operable enterprise systems environment. This position supports the development, automation, deployment, and maintenance of enterprise integrations and applications across the university’s technology ecosystem. This role is designed for early-career professionals with foundational technical experience who are eager to grow their skills in a real-world, AI-forward enterprise setting. The DevOps Engineer I works within an established engineering team to help design, build, document, and operate governed AI tools, integrations, and automations that connect Florida Poly’s enterprise systems including Ellucian Banner, Workday, Salesforce, and Microsoft Azure. Work is performed using GitHub-centered engineering practices, including version-controlled code, pull request review, CI/CD pipelines, and structured documentation. The DevOps Engineer I contributes to agentic AI pilots such as building read-only knowledge tools, producing AI-assisted recommendations, drafting actions, and supporting human-approved execution workflows. This role is an opportunity to grow alongside an emerging discipline, gain hands-on experience with MCP servers, OpenAPI tool definitions, Azure Foundry, and AI-assisted development, and help shape how a modern STEM university operates its enterprise technology.

Requirements

Bachelor’s Degree in Computer Science, Computer Engineering, Information Systems, or a related analytical field, or equivalent experience.
Entry-level to 3 years of relevant experience in software development, DevOps, cloud services, systems integration, automation, or related technical work.
Experience may include internships, student employment, capstone projects, research projects, open-source contributions, or personal technical projects.
Foundational software engineering skills, including coding, testing, version control, and GitHub-based or similar development workflows.
Working knowledge of APIs, REST principles, and structured data exchange formats (JSON, XML).
Familiarity with cloud platforms, particularly Microsoft Azure; experience with Azure Functions, Logic Apps, or similar services is a plus.
Exposure to or genuine interest in agentic AI, large language models (LLMs), MCP servers, or OpenAPI tool definitions.
Ability to write clear, structured technical documentation intended for both human and AI audiences.
Proven ability to learn and master new technologies quickly.
Excellent communication and collaboration skills, both verbal and written, and the ability to work closely with team members.
Excellent analytical and problem-solving skills.
Strong attention to detail.
Must possess a valid driver’s license.
This position requires a criminal background check, which may include a Level II screening as required by Florida Statute §435.04.
This position is subject to federal and state privacy regulations.

Nice To Haves

Experience with GitHub, CI/CD concepts, automated testing, and deployment pipelines.
Exposure to AI-assisted software development using tools such as Claude Code, GitHub Copilot, or similar platforms.
Interest in building secure, AI-ready integrations and applications that can be operated by humans today and AI agents in the future.
Experience with cloud applications and SaaS platforms such as Microsoft Azure, Ellucian Banner, Workday, or Salesforce

Responsibilities

Contribute to the design, implementation, testing, and documentation of governed AI tools, integrations, and automations using approved DevOps practices, following secure coding and change control standards.
Assist in building and operating pilot AI agent workflows, including read-only knowledge tools, recommendation systems, and draft-action workflows, and help design integrations that are AI-ready, well-documented, and suitable for future automation.
Create and maintain structured technical documentation, including README files, runbooks, architecture notes, and operational procedures, written clearly enough for both human engineers and AI-assisted development tools.
Respond to integration issue reports, assist in diagnosing failures, and support operational reliability by helping improve monitoring, alerting, logging, and visibility across the team’s portfolio of integrations and applications.