University of Central Florida

University of Central Florida

AI Automation Designer I

Orlando, FL (Main Campus), USA · Junior

No sponsorship$56k-$62kDetected 3 days ago
PythonAWSAzureCloud PlatformsMachine LearningLLMsAI OrchestrationSystems EngineeringResearchCommunicationCollaboration

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odds of building a lasting career here

88Lottery-free
Cap-exempt (no lottery)100
Sponsors year-round90
Entry-level history60
PERM / green-card track50
Fits your clock70

Files H-1B any time — no cap, no lottery. The 2026 weighted-selection rule doesn't touch it, which makes this the strongest structural path for entry-level talent. Pay is often lower, but your odds of staying are dramatically higher.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

States it is exempt from the H-1B cap

In 43 Department of Labor filings, this employer states it is an institution of higher education — one of the statutory grounds for exemption from the H-1B cap. Cap-exempt employers can file year-round without entering the lottery.Employer's own attestation on a Department of Labor wage determination, not a USCIS determination — exemption is decided per petition.

Files H-1B transfers

1 transfer filing in the last year, covering 1 worker. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • The UCF IT department within University Operations is seeking to hire anAI Automation Designer I.

Responsibilities

  • Partner with members of the AI Center of Excellence and administrative teams to identify and design high-impact automation opportunities that deliver measurable business value.
  • Design, develop, and deploy automation solutions using low-code RPA tools (e.g., Microsoft Power Automate), Python scripting, and AI/ML capabilities in Azure (e.g., Microsoft Foundry).
  • Create reusable playbooks, agent templates, and modules (e.g., FAQ agents, tool-invoking agents, knowledge bots) for replication across departments.
  • Support deployment, testing, and roll-out of AI/agent workflows, including logging, error handling, fallback strategies, and quality assurance.
  • The position exists to deliver automation solutions and to establish repeatable patterns that can be leveraged for future automation deployments.

Requirements

  • Bachelor's degree
  • or High School Diploma (or equivalent) and 4 years of relevant work experience in lieu of degree

Nice to have

  • Experience working with large language models (LLMs),
  • Familiarity with Microsoft, Azure, or other hyperscale cloud environments such as AWS or GCP.
  • Special Instructions to the Applicants:
  • We urge you to please take the time to complete the application in its entirety.
  • All applicants must be authorized to work for any U.S. employer.
  • Visa sponsorship is not available for this position, and the university cannot accommodate H‑1B transfers or employment-based visa processing for individuals currently sponsored by another employer.
  • Classification Title: Systems Engineer I
  • Are you ready to unleash YOUR potential?

Compensation

  • The anticipated salary range for this position is $56,030 - $62,000.

Company info

  • University Operations at UCF is committed to creating a supportive and welcoming environment for our faculty, staff, students, and the broader community.
  • This role is responsible for serving as part of the university's AI Center of Excellence, embedding with administrative teams to design, implement, and promote AI-enabled process automations and workflows.

Visa & Work Authorization

  • All applicants must be authorized to work for any U.S. employer.

This listing is sourced directly from University of Central Florida's careers page and normalized into a canonical job model.