AI Operations Analyst

Location: Austin, TX - USA

Reports To: VP, Enterprise AI & Automation

Salary Range: $106,000 - 132,000

IEM is seeking a driven AI Operations Analyst to turn practical AI opportunities into working solutions. You will be the entry point for new AI ideas, guide the promising ones through prototyping, and help employees adopt what gets built.

You will also own the enablement work behind those tools: access, licenses, onboarding and offboarding. Success means learning that work, then simplifying or automating it.

We want someone who sees how a business process actually works and instinctively looks for a better way to run it, whether that is an AI model, an agent, a workflow automation, an API integration, or a small custom application. You do not need to be a senior software engineer, but you should learn fast and enjoy building.

This is a visible, hands-on role for someone already experimenting with these tools who wants to shape how a growing enterprise adopts AI.

This role requires a work sample. Applications submitted without one will not be reviewed — see “How to Apply” below.

The first three areas are the core of the role and the primary basis for evaluating performance.

• Process Discovery: Partner with teams across IEM to find manual, repetitive, or error-prone work, and determine whether AI, automation, integration, or process redesign is the right fix.
• Solution Development: Design, build, test, and deploy practical solutions using AI tools, workflow automation, agents, and APIs, then maintain and improve them after launch.
• Measurement & Continuous Improvement: Define success measures such as time saved, errors reduced, and adoption, then improve, expand, or retire solutions based on what they demonstrably deliver.
• AI Project Intake & Prioritization: Serve as the entry point for new AI requests, separating genuine business needs from interest in a particular tool, and prioritize what moves forward.
• AI Literacy, Training & Enablement: Deliver onboarding, workshops, and training that build real proficiency with approved AI tools, and help employees build their own automations.
• AI Platform Operations: Run day-to-day administration of IEM’s AI platforms, and keep procedures, FAQs, and adoption reporting current.
• Access & License Management: Manage access requests and approvals, provision and reclaim licenses, and flag underused or overallocated seats.
• Governance & Compliance: Confirm that AI tools, user access, and deployed solutions meet IEM’s AI governance and data security standards, and escalate exceptions.

• AI Mindset: You always invite AI to the table as a thinking partner—experimenting broadly while keeping human judgment in the lead.
• Proven AI Implementation: You’ve put an AI solution into real use inside an organization—one others relied on—while navigating stakeholder needs, budget limits, and security requirements.
• Practical Technical Judgment: You know when AI is not the right tool, and can weigh accuracy, cost, privacy, security, and how much human oversight a solution needs.
• AI & Automation Tool Fluency: You have hands-on knowledge of generative AI tools, automation platforms, APIs, and business-system integrations—and can quickly learn new ones.
• Relevant Experience: You’ve worked in operations, process improvement, automation, or IT. What you’ve built matters more than years served.
• Organization & Follow-Through: You prioritize competing work, document it, and finish it.
• Communication & Enablement: You explain technical concepts plainly to non-technical colleagues.

• Track record as the go-to AI or automation resource on a team.
• Requirements gathering, process mapping, or change management support.
• Python, TypeScript, low-code automation, AI agents, APIs, or system integrations.
• Reporting or operational data analysis with Excel, SQL, or similar tools.
• Experience in manufacturing or other environments where employees are not desk-based.
• Coursework or certifications in AI or project management; applied work weighs more.

• Bias Toward Action: Builds the small version and shows it instead of scheduling a meeting.
• Business Impact Orientation: Prioritizes measurable gains in productivity, quality, or cost.
• User-Centered Communication: Listens well, asks good questions, treats people with respect.
• Problem-Solving & Adaptability: Troubleshoots methodically, escalates early, learns fast.
• Operational Discipline: Documents accurately, tracks details, finishes what is started.

• Position is located in Austin, TX, and is primarily in-person.
• Some travel is required to IEM facilities or for project kickoffs.
• Interviews are conducted in person in Austin.

• Competitive salary and benefits package commensurate with experience.
• Meaningful ownership of solutions with visible, measurable business impact.
• Exposure to teams, workflows, and challenges across the organization.
• Direct mentorship from senior AI and technical staff.
• Opportunities to experiment, build, and grow into more advanced AI, automation, or engineering roles.
• Professional development, training resources, and hands-on access to enterprise AI tools and platforms.

Submit your resume and a work sample. Applications without a work sample will not be reviewed.

A work sample is anything that lets us see what you built and how you think. The options below are listed in order of preference:

1. A link to a repository, live tool, or published project.
2. A short screen recording—roughly five minutes—showing something you built and explaining your decisions. It does not need to be polished.
3. A brief written case study of an AI or automation solution you implemented: the problem, your role, what you built, the constraints you navigated, and what changed.

Submit work you personally scoped and built. If it was part of a team effort, clearly explain what you owned. Samples demonstrating independent ownership and execution will carry the most weight.

We value independent judgment; a small solution you built yourself is more useful than a course project, tutorial, or forked repository.

If your strongest work is confidential or proprietary, submit a sanitized reconstruction or short case study. Do not disclose confidential information or provide access to a current or former employer’s systems.

We would rather see something rough and real than polished and generic.