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Ai Automation Testing Jobs in Florida (NOW HIRING)

Several approved AI use cases have moved from discovery and design through testing, rollout, and ... Experience with automation platforms such as Microsoft Power Automate, Power Platform, UiPath ...

AI & Automation Implementation * Build, implement, and maintain AI-enabled automation workflows ... testing coordination, rollout planning, and post-launch support activities * Track action items ...

AI & Automation Implementation * Build, implement, and maintain AI-enabled automation workflows ... testing coordination, rollout planning, and post-launch support activities * Track action items ...

AI & Automation Implementation * Build, implement, and maintain AI-enabled automation workflows ... testing coordination, rollout planning, and post-launch support activities * Track action items ...

Strategic AI & Automation Leadership * Develop and execute the Health Plan's AI and automation ... Create repeatable frameworks for evaluating, testing, and operationalizing emerging technologies.

WAI is investing in AI, automation, data, and digital capabilities that can improve how work gets ... Experience supporting offshore delivery, remote collaboration, documentation, testing, or ...

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Ai Automation Testing information

What are some common challenges faced by AI Automation Testing professionals when validating machine learning models?

AI Automation Testing professionals often encounter challenges such as ensuring that test cases comprehensively cover the unique behaviors of machine learning models, dealing with non-deterministic outputs, and handling large datasets efficiently. It's also common to face difficulties in setting up reliable test environments that simulate real-world data scenarios. Collaboration with data scientists and developers is crucial to define meaningful metrics and effectively interpret test results, ensuring the AI system meets both functional and ethical standards.

What is AI automation testing?

AI automation testing refers to the use of artificial intelligence technologies to automate the process of testing software applications. This approach enhances traditional automated testing by using machine learning and data analysis to identify test cases, detect defects, and optimize test coverage. AI-driven testing tools can adapt to changes in the application, reduce manual effort, and improve the accuracy and speed of testing processes. As a result, organizations can deliver higher-quality software more efficiently.

How much do AI testers get paid?

AI automation testers typically earn between $60,000 and $120,000 annually, depending on experience, location, and skill level. Entry-level positions may start around $50,000, while experienced professionals with skills in machine learning and scripting can earn higher salaries. Certifications and proficiency with testing tools can also influence compensation.

What are the key skills and qualifications needed to thrive as an AI Automation Testing professional, and why are they important?

To thrive as an AI Automation Testing professional, you need a solid understanding of software testing principles, programming languages (such as Python or Java), and AI/ML concepts, often supported by a degree in computer science or a related field. Familiarity with automation tools like Selenium, Appium, and AI-powered testing frameworks, as well as certifications like ISTQB, is highly valued. Strong analytical thinking, attention to detail, and effective communication skills help professionals excel in diagnosing issues and collaborating with development teams. These skills ensure the delivery of robust, efficient, and reliable AI-driven software products in a competitive technology landscape.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as AI research director, senior machine learning engineer, or AI executive, often requiring advanced skills, extensive experience, and sometimes leadership responsibilities. Such roles usually involve developing innovative AI solutions, managing teams, and may require expertise in programming, data analysis, and relevant tools like TensorFlow or PyTorch.

Is AI testing a good career?

AI automation testing is a growing field that involves evaluating AI systems for accuracy, reliability, and performance using tools like scripting and testing frameworks. It offers opportunities in technology companies, with demand increasing as AI applications expand across industries. Developing skills in programming, machine learning concepts, and testing tools can enhance career prospects in this area.

What is the difference between Ai Automation Testing vs Software Test Engineer?

AspectAi Automation TestingSoftware Test Engineer
Required CredentialsCertifications in AI, automation tools, programming languagesSoftware testing certifications (ISTQB, CSTE), programming skills
Work EnvironmentFocus on automation frameworks, AI integration, scriptingManual and automated testing, test case design, bug tracking
Employer & Industry UsageTech companies, AI-driven projects, software development firmsSoftware development companies, IT departments, QA teams

Ai Automation Testing and Software Test Engineer roles overlap in testing skills and programming knowledge. However, Ai Automation Testing emphasizes AI integration and automation frameworks, while Software Test Engineers focus more on manual testing, test case creation, and bug identification. Both roles are essential in software quality assurance but serve different aspects of the testing process.

What cities in Florida are hiring for Ai Automation Testing jobs? Cities in Florida with the most Ai Automation Testing job openings:
Infographic showing various Ai Automation Testing job openings in Florida as of July 2026, with employment types broken down into 74% Full Time, 23% Part Time, and 3% Contract. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution.
Manager, AI Automation Engineer

Manager, AI Automation Engineer

WAI Global

Miramar, FL • On-site

Full-time

Posted 27 days ago


Job description

Job Type
Full-time
Description
About WAI
Since 1978, WAI has grown from an entrepreneurial start-up into a global aftermarket leader headquartered in South Florida. Nearly five decades of product knowledge, customer trust, and operational scale now support an ambitious growth agenda across distribution, manufacturing, product, customer, supply chain, and shared-service operations.
That scale creates a meaningful opportunity for practical enterprise AI. WAI is investing in AI, automation, data, and digital capabilities that can improve how work gets done: reducing manual effort, increasing speed and quality, strengthening decision-making, and helping teams serve customers more effectively.
About the Role
WAI is creating new enterprise AI capability focused on practical business impact: improving workflows, reducing manual effort, increasing speed and quality, supporting better decisions, and helping teams use AI-enabled tools responsibly.
The Manager, AI Automation Engineering is a hands-on, business-facing delivery role responsible for turning approved AI-enabled use cases into working workflows, tools, and supportable solutions. You will help design, build, configure, test, launch, document, and continuously improve AI-enabled workflows across WAI.
This role supports the business side of a business-led, IT-governed operating model. You will work closely with the Director, Enterprise AI Automation & Transformation, business stakeholders, IT, data, security, AI platform resources, vendors, offshore or remote technical resources, and users to ensure solutions are practical, secure, adopted, supportable, and aligned with enterprise standards.
This is a player-coach role for someone who enjoys both the business and technical sides of AI and automation. You should be comfortable sitting with a business team to understand a manual process, translating that process into a practical workflow design, building or coordinating the solution, testing it carefully, documenting how it works, and helping users adopt it successfully.
Why This Role Matters
AI will create the most value at WAI when it is connected to real workflows, trusted data, clear controls, strong adoption, and measurable results.
In this role, you will help WAI move from AI interest to AI operating discipline by turning prioritized opportunities into solutions teams can actually use. Great AI-enabled workflows are not just prompts, prototypes, or demos. They require process understanding, clear requirements, tested outputs, secure data handling, human review, documented logic, user training, support procedures, and continuous improvement.
We care as much about reliable adoption as we do about clever prototypes.
What You'll Do
Manage and support the design, build, implementation, rollout, and continuous improvement of AI-enabled workflows, internal productivity tools, and agent-based solutions across multiple business functions.
Partner with business stakeholders to understand process pain points, manual work, decision points, workflow dependencies, controls, exceptions, and improvement opportunities.
Translate business needs into practical workflow steps, prompts, business rules, logic, integrations, user-facing experiences, test plans, acceptance criteria, documentation, and support procedures.
Build, configure, or help maintain AI-enabled workflows using approved AI tools, workflow platforms, scripts, APIs, enterprise systems, and other technical building blocks.
Lead or support discovery sessions, process mapping, future-state workflow design, solution design documentation, testing, rollout planning, training, feedback collection, and benefit tracking.
Configure or guide prompt flows, workflow logic, tool usage, escalation paths, source citation, human-in-the-loop steps, and other controls in alignment with WAI's AI governance expectations.
Coordinate with IT, data, security, AI platform resources, offshore engineers, and external partners on access, integrations, architecture review, production readiness, delivery execution, and ongoing support.
Test solutions for accuracy, reliability, usability, data handling, security considerations, and alignment with business requirements before deployment.
Monitor live solutions, troubleshoot issues, document defects, gather user feedback, recommend improvements, and help ensure workflows continue to perform as business needs evolve.
As the program scales, provide coaching, day-to-day direction, or performance input for AI Automation Engineers, project contributors, vendors, or remote delivery resources as assigned.
What You'll Build or Own
You will help execute the operating model for enterprise AI adoption at WAI by turning approved use cases into working solutions that business teams can trust.
  • AI-enabled workflows across business functions
  • Internal productivity tools and business-facing copilots
  • Prompt flows, workflow logic, business rules, integrations, and escalation paths
  • Retrieval or knowledge-based workflows where trusted source material matters
  • Human-in-the-loop review steps and control points
  • Test plans, acceptance criteria, validation routines, and defect documentation
  • Workflow, prompt, rule, integration, user procedure, and support documentation
  • Rollout materials, training content, adoption support, and feedback loops
  • Monitoring, troubleshooting, and continuous improvement processes
  • Reusable delivery patterns that help WAI scale AI adoption responsibly

This role works closely with IT and AI platform resources on architecture, access, security, integrations, and production readiness, while staying focused on practical business workflow delivery.
What Success Looks Like
In the first 6-12 months, success looks like:
  • Several approved AI use cases have moved from discovery and design through testing, rollout, and improvement.
  • Practical solutions are saving time, reducing manual work, improving consistency, improving service quality, or helping teams make better decisions.
  • Business users understand how to use the new workflows and know when human review, escalation, or exception handling is required.
  • Clear documentation exists for workflows, business rules, prompts, testing, support procedures, and ongoing maintenance.
  • IT, AI platform resources, offshore engineers, and business stakeholders are aligned on delivery expectations, access, controls, and production readiness.
  • Live solutions are monitored, issues are addressed, user feedback is captured, and improvements are made over time.
  • WAI has stronger repeatable delivery patterns for building, testing, launching, and supporting AI-enabled workflows.

Requirements
What We're Looking For
We are looking for a hands-on AI and automation delivery leader who can combine technical fluency, business curiosity, structured problem-solving, and strong follow-through.
Strong candidates will have experience building, configuring, supporting, or leading workflow automation, AI-enabled tools, business systems, data workflows, application integrations, internal tools, or similar technical/business transformation work.
You should be able to translate business problems into workflows, requirements, prompts, rules, integrations, test plans, acceptance criteria, documentation, and implementation steps.
You should have hands-on fluency with AI-enabled workflows using some combination of large language models, prompt design, retrieval-augmented generation, chatbots, AI agents, workflow orchestration, or similar approaches.
You should have working knowledge of technical building blocks such as APIs, JSON, scripting, SQL, Python, workflow automation tools, enterprise systems, or similar capabilities. You do not need to be a traditional software engineering manager, but you should be technical enough to build, configure, test, troubleshoot, document, and guide AI-enabled workflow delivery.
You should be comfortable working with both technical and non-technical stakeholders, including business users, functional leaders, process owners, IT, data/security partners, vendors, and remote or offshore technical resources.
You should bring strong judgment about when automation is appropriate, when human review or escalation is needed, and how to balance speed, usability, reliability, data handling, controls, and long-term scalability.
You should be organized, detail-oriented, collaborative, and energized by a fast-changing AI environment where standards and delivery patterns are still being built.
Nice-to-Have Experience
  • Experience with automation platforms such as Microsoft Power Automate, Power Platform, UiPath, Zapier, Workato, Make, or similar tools.
  • Experience with AI tools or platforms such as Microsoft Copilot Studio, Azure AI, Enterprise LLM tools, RAG frameworks, agent orchestration tools, workflow tools, or similar technologies.
  • Experience working with operational functions such as Customer Service, Supply Chain, Finance, HR, Sales Support, Product/Catalog, Operations, Shared Services, manufacturing, distribution, or other complex business environments.
  • Experience coordinating offshore or remote technical resources, vendors, implementation partners, or cross-functional project teams.
  • Experience coaching engineers, analysts, citizen developers, project contributors, or business users.
  • Certifications or formal training in Microsoft Power Platform, Azure AI, automation platforms, project management, data analytics, Lean/Six Sigma, business process management, or related technical areas.

We know strong candidates may come from different paths, including automation engineering, business systems, solution engineering, applied AI, data workflows, process improvement, technical consulting, internal tools, or enterprise technology delivery. You do not need to have used every tool listed here. We care most about your ability to turn business problems into trusted, tested, adopted AI-enabled workflows.
Education and Experience
A bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, Business Systems, Operations, or a related field is preferred. Equivalent hands-on experience may be considered.
Experience in automation, AI-enabled tools, software development, business systems, process improvement, data workflows, workflow tools, application integration, or a related technical/business transformation role is expected.
Working Model and Travel
This is an onsite, business-facing role that requires close collaboration with business users, functional leaders, process owners, IT, remote technical resources, vendors, and cross-functional project teams.
Limited travel may be required, estimated at approximately 0-10%, based on business needs, project rollout requirements, training, workshops, or site visits.
Why WAI
  • Growth and Scale - WAI combines the complexity of a global operating business with the opportunity to build new AI and digital capabilities from the ground up.
  • Autonomy and Impact - These roles offer the chance to shape new capabilities, influence how teams work, and create visible business impact.
  • Practical Innovation - WAI is focused on AI that improves real workflows, trusted data, productivity, quality, service, and operational execution.
  • Global Business Context - You will work on challenges connected to products, customers, inventory, supply chain, manufacturing, distribution, and enterprise operations.
  • Responsible AI Adoption - WAI is building AI capabilities with attention to governance, human review, data quality, security, adoption, and measurable value.

WAI is an Equal Opportunity Employer. We are committed to providing equal employment opportunities to all applicants and employees without regard to any characteristic protected by applicable federal, state, or local law.