> Markdown version of [/jobs/ext/4463739-ai-automation-analyst](https://www.wearedevelopers.com/jobs/ext/4463739-ai-automation-analyst). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Automation Analyst - **Company:** SouthernCarlson, Inc. - **Location:** La Vista, NE, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Business Systems, Databases, Cursor, Python (Programming Language), PostgreSQL, Microsoft SQL Server, NoSQL, Power BI, Systems Integration, Scripting, Microsoft Power Automate, Large Language Models, Claude Code, Prompt Engineering, Zapier, AI Coding Agents, Data Analytics, Performance Monitor, Claude, GPT - **Published:** October 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=75da83a66990bf93 ## About the Role Required * 3+ years in business process analysis, business systems, or operations, in a role where you built things rather than only recommended them * Hands-on database experience, ideally PostgreSQL or SQL Server; exposure to NoSQL or document stores is useful * Working Python skills: able to write and modify scripts that move, transform, and validate data * Hands-on experience with LLM APIs, including prompt design and structured outputs, not just chat-window usage * Daily use of AI coding assistants (such as Cursor, Claude Code, ChatGPT, or Claude) to build real working output. * Experience integrating systems through APIs, files, or a platform such as Workato, Power Automate, or Zapier * Experience with ERP or other business systems, and the judgment to spot bad data before it becomes a bad automation * Ability to tell a business owner their process should change, and bring them along rather than steamroll them * Ability to train non-technical users and get them to actually adopt what you built * Willingness to travel up to 25% to branch and regional locations * High school diploma or equivalent; Associate's or Bachelor's degree preferred Preferred * Experience in distribution, industrial, construction supply, or building materials industry * Business intelligence tools (Power BI or similar), or document processing work such as PDF extraction and OCR * A track record of automation work you can point to and quantify ## Description The AI Automation Analyst will identify opportunities to streamline and improve business operations through AI, automation, and data-driven solutions. This role partners with teams across the organization to analyze workflows, uncover inefficiencies, and design, build, test, and implement automation solutions using Python, LLM technologies, databases, and systems integrations. The position owns the full automation lifecycle, including requirements gathering, solution development, user training, performance monitoring, and continuous improvement, while measuring business impact and prioritizing initiatives that deliver the greatest operational value. Responsibilities * Work with teams across the business to map how work actually gets done, including the routine, repetitive, and duplicated effort nobody wrote down * Analyze those workflows to define the real problem, trace it back to the data behind it, and prioritize use cases on value, impact, feasibility, and risk * Build the solutions: Python scripts and LLM pipelines that classify, extract, match, and validate data, plus the automations and review screens that go with them * Document requirements and own design, configuration, and rollout alongside the teams who will use the result * Build the business case: cost-benefit analysis, implementation plan, and the measures of success * Test AI output against known-good results before go-live, run UAT with business users, and set the thresholds for what is auto-approved versus routed to a human * Train users and build their confidence with AI-enabled tools through hands-on sessions, documentation, and ongoing support * Monitor usage and performance after launch, catch failures and drift, and act on improvement opportunities * Measure and report the impact: time returned to the team, errors avoided, and work made possible that was not before * Stay current on emerging AI tools and platforms, and make recommendations on what we should adopt * Own the automation backlog and make the call on what gets built next