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Ai Operations Jobs (NOW HIRING)

Job Title:- AI Operations Analyst Location:- Spring Texas (100% On-Site) Job Type:- Long Term Contract Employment type:W2 Visa: USC,GC,GC-EAD,H4-EAD The role is not looking for an AI Engineer.

AI Operations

New York, NY · On-site

$100K - $300K/yr

About the Role AI Operations is a builder's role for helping patients get access to medicine. You will take responsibility for live operational problems: a workflow to improve, a process to scale, or ...

AI Operations Lead

San Francisco, CA · On-site

$150K - $200K/yr

The Role We are hiring an AI Operations Lead to build the internal systems that enable Broccoli to scale. As we 5x headcount in 2026, leverage is everything: the dashboards, tools, and AI agents that ...

AI Operations Lead

San Francisco, CA · On-site

$150K - $190K/yr

What You'll Bring * 2-5+ years of experience in business operations, strategy, technical program management, or applied AI, with hands-on building experience. * Demonstrated experience shipping AI ...

Associate AI Operations Customer Experience | Provo, UT | Full-Time | On-Site | $50,000 - $90,000 | Entry-Level / 0-2 Years ABOUT ATONOM Atonom.ai builds Cloud Employees: intelligent AI agents that ...

AI Operations Associate

San Jose, CA · On-site

$90K - $110K/yr

Role Description You'll join our AI operations team as we scale it up. You'll be the bridge between how healthcare work actually gets done and how our AI learns to do it: sitting with customers to ...

Role Description You'll join our AI operations team as we scale it up. You'll be the bridge between how healthcare work actually gets done and how our AI learns to do it: sitting with customers to ...

AI Operations Associate

Fremont, CA · On-site

$90K - $110K/yr

Role Description You'll join our AI operations team as we scale it up. You'll be the bridge between how healthcare work actually gets done and how our AI learns to do it: sitting with customers to ...

AI Operations Associate

Alameda, CA · On-site

$90K - $110K/yr

Role Description You'll join our AI operations team as we scale it up. You'll be the bridge between how healthcare work actually gets done and how our AI learns to do it: sitting with customers to ...

AI Operations Associate

Sonoma, CA · On-site

$90K - $110K/yr

Role Description You'll join our AI operations team as we scale it up. You'll be the bridge between how healthcare work actually gets done and how our AI learns to do it: sitting with customers to ...

AI Operations Associate

Santa Clara, CA · On-site

$90K - $110K/yr

Role Description You'll join our AI operations team as we scale it up. You'll be the bridge between how healthcare work actually gets done and how our AI learns to do it: sitting with customers to ...

AI Operations Associate

Santa Rosa, CA · On-site

$90K - $110K/yr

Role Description You'll join our AI operations team as we scale it up. You'll be the bridge between how healthcare work actually gets done and how our AI learns to do it: sitting with customers to ...

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Ai Operations information

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How much do ai operations jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for ai operations in the United States is $24.15, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $27.64 per hour, depending on experience, location, and employer.

What is AI Operations?

AI Operations, often referred to as AIOps, is the use of artificial intelligence and machine learning technologies to automate and enhance IT operations. It involves analyzing large volumes of data generated by IT systems to detect issues, predict outages, and automate responses. AIOps helps organizations improve efficiency, reduce downtime, and quickly resolve problems by providing actionable insights and automating repetitive tasks. This approach is increasingly important as IT environments become more complex and data-driven.

How does an AI Operations professional typically collaborate with data scientists and IT teams?

AI Operations professionals often act as a bridge between data science teams, who develop machine learning models, and IT teams, who manage infrastructure. They work closely to ensure models are deployed smoothly, monitored for performance, and integrated into production environments. Regular communication and troubleshooting are essential, as AI Ops professionals must understand both the technical requirements of the models and the operational constraints of the systems. This collaborative approach helps maintain reliability and scalability of AI solutions in a business setting.

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

To thrive in AI Operations, you need a strong background in computer science, data analytics, and machine learning, often supported by a degree in a related field. Familiarity with tools like Python, TensorFlow, cloud platforms (e.g., AWS, Azure), and experience with AI/ML monitoring systems is essential. Critical thinking, problem-solving, and effective communication are key soft skills for managing incidents and collaborating with cross-functional teams. These skills ensure the smooth deployment, monitoring, and optimization of AI systems, which are vital for operational reliability and business success.

What is the difference between Ai Operations vs Data Scientist?

AspectAi OperationsData Scientist
Required CredentialsCertifications in AI/ML, programming skillsStatistics, data analysis, programming
Work EnvironmentOperational teams, AI deployment, maintenanceResearch, data analysis, modeling
Industry UsageAI system management, deployment, monitoringData analysis, predictive modeling, research

Ai Operations focuses on managing and maintaining AI systems in production, ensuring their performance and reliability. Data Scientists primarily analyze data, develop models, and generate insights. While both roles require technical skills and programming knowledge, Ai Operations emphasizes deployment and operational stability, whereas Data Scientists focus on data analysis and model development.

More about Ai Operations jobs

What cities are hiring for Ai Operations jobs?

Cities with the most Ai Operations job openings:

What are the most commonly searched types of Ai Operations jobs?

The most popular types of Ai Operations jobs are:

What states have the most Ai Operations jobs?

States with the most job openings for Ai Operations jobs include:

Infographic showing various Ai Operations job openings in the United States as of August 2026, with employment types broken down into 84% Full Time, 13% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $50,239 per year, or $24.2 per hour.

Full-time

Medical, Retirement

Re-posted 14 days ago


Holland America Line rating

6.2

Company rating: 6.2 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

7th of 9 rated cruise lines


Job description

Manager, AI Operations

Holland America Line has been exploring the world since 1873. Our ships offer innovative features and enriching experiences focused on destination exploration and personalized travel, inviting guests to savor the journey.

The Manager, AI Operations establishes and leads the business-side operating function required to turn enterprise AI capabilities into measurable, adopted, and sustainable ways of working. This role bridges AI Innovation, IT, PMO, commercial/product stakeholders, and business operations by defining the value case for AI work, translating scaled technology into operational implementation plans, and building the change, training, readiness, hypercare, and sustainment practices that enable teams to use AI effectively. As AI adoption expands, this leader will develop the standards, processes, tools, routines, and team capabilities needed to scale AI implementation across the organization. The role manages direct reports, provides strategic and operational leadership through ambiguity, and ensures AI initiatives move beyond pilots and technology delivery to realized business outcomes.

Responsibilities:

AI Operations Strategy & Operating Model

  • Establish the business-side AI Operations function, including its service model, intake criteria, implementation standards, readiness criteria, launch playbooks, and success measures.
  • Define how AI solutions transition from innovation and IT scaling into business ownership, including roles, responsibilities, decision rights, handoff requirements, support models, and sustainment expectations.
  • Build repeatable frameworks for AI operational readiness, including process impacts, workflow changes, role impacts, controls, adoption risks, training needs, communications needs, data considerations, and support requirements.
  • Develop the organizational skillsets required to implement AI at scale, including AI change management, adoption analytics, prompt/tool usage standards, human-in-the-loop operations, business process redesign, and responsible AI ways of working.
  • Lead and coach direct reports responsible for implementation planning, adoption support, KPI tracking, training coordination, stakeholder readiness, and operational sustainment.
  • Anticipate future AI operating needs as adoption expands and proactively build scalable tools, processes, templates, and capabilities that can be reused across brands, functions, and teams.

Business Implementation

  • Own the business implementation plan for AI capabilities after IT scaling, including launch planning, stakeholder readiness, business cutover, operational communications, training approach, support model, and hypercare execution.
  • Translate AI capabilities into practical business usage by defining who will use the tool, when it will be used, what decisions or workflows it supports, what behaviors need to change, and how performance will be measured.
  • Partner with business operations, functional leaders, learning/training teams, IT, and AI Innovation to develop enablement content, job aids, user guidance, FAQs, readiness checklists, office hours, and adoption support materials.
  • Lead change-impact assessments and stakeholder adoption plans for AI initiatives, including readiness risks, resistance points, workforce implications, governance requirements, and operational dependencies.
  • Manage hypercare after launch, including issue triage, user feedback loops, adoption monitoring, escalation paths, enhancement requests, and transition to steady-state support.
  • Ensure AI implementations are usable, supportable, and embedded into day-to-day business processes rather than remaining isolated tools or one-time pilots.

Product Sustainment & Continuous Improvement

  • Define sustainment requirements for AI-enabled tools and processes, including ownership, documentation, support channels, refresh cadence, usage monitoring, escalation paths, and enhancement governance.
  • Build feedback mechanisms to understand user experience, adoption barriers, process friction, content gaps, quality issues, and opportunities for automation or workflow redesign.
  • Partner with IT and AI Innovation to ensure business feedback, operational defects, usage patterns, and enhancement opportunities are incorporated into product backlogs and lifecycle planning.
  • Establish operational controls for responsible use, including user guidance, approval paths, data handling expectations, auditability needs, human review points, and alignment with enterprise AI governance.
  • Maintain implementation assets and knowledge repositories so teams can reuse proven approaches, avoid duplicated effort, and scale AI adoption more consistently.
  • Drive continuous improvement of the AI Operations function by assessing what worked, what did not, and how future deployments can be faster, safer, clearer, and more valuable.

Knowledge & Skills:

  • Scope: The Manager, AI Operations establishes and leads the business-side operating function required to turn enterprise AI capabilities into measurable, adopted, and sustainable ways of working. This role bridges AI Innovation, IT, PMO, commercial/product stakeholders, and business operations by defining the value case for AI work, translating scaled technology into operational implementation plans, and building the change, training, readiness, hypercare, and sustainment practices that enable teams to use AI effectively. As AI adoption expands, this leader will develop the standards, processes, tools, routines, and team capabilities needed to scale AI implementation across the organization. The role manages direct reports, provides strategic and operational leadership through ambiguity, and ensures AI initiatives move beyond pilots and technology delivery to realized business outcomes.
  • Problem solving: Solves complex, ambiguous, and often unprecedented implementation challenges where AI technology, business process, workforce readiness, operational risk, adoption behavior, and value measurement intersect. Translates unclear or emerging AI opportunities into structured business cases, KPI frameworks, operating requirements, change plans, and sustainment models. Anticipates downstream barriers before launch and develops practical solutions when no established playbook exists.
  • Impact: Has significant influence on whether AI investments move from concept and technology delivery into adopted, measurable, and scalable business outcomes. Provides decisions and recommendations that affect portfolio prioritization, business readiness, implementation sequencing, adoption effectiveness, operational continuity, employee capability, benefit realization, and the organization's long-term ability to implement AI responsibly and repeatedly.
  • Leadership: Provides direct supervision, coaching, prioritization, workload management, and capability development for AI Operations team members. Leads through influence with senior stakeholders and cross-functional teams, often without direct authority, to align implementation plans, adoption expectations, value measures, support models, and decision-making. Builds a team culture focused on disciplined execution, practical business adoption, responsible AI use, continuous learning, and scalable operating practices.

Qualifications:

  • Bachelor's Degree in Accounting, Information Technology, or related field; advanced Bachelor's degree in Business Administration, Operations, Technology Management, Change Management, Organizational Effectiveness, Product Management, Analytics, or related field required; advanced degree preferred.
  • Demonstrated ability to build new operational capabilities, frameworks, processes, or teams in a changing business environment.
  • Strong understanding of business case development, KPI design, benefits realization, change management, implementation planning, and operational readiness.
  • Experience leading direct reports and developing team capabilities, performance, priorities, and ways of working.
  • Ability to partner effectively with technology, product, PMO, operations, learning/training, analytics, and senior business stakeholders.
  • Familiarity with AI, automation, digital transformation, product lifecycle, or technology implementation preferred; hands-on AI development experience is not required.

Essential Experience Required:

  • 8+ years of progressive experience in business operations, transformation, implementation, change management, PMO, product operations, technology adoption, consulting, or related roles.
  • 3+ years of people leadership experience or equivalent experience leading cross-functional teams, workstreams, or implementation teams.
  • Experience developing business cases, KPIs, adoption metrics, benefits tracking, executive updates, or portfolio prioritization inputs.
  • Experience implementing new tools, processes, operating models, or technology-enabled capabilities into business teams, including training, communications, readiness, launch, hypercare, and sustainment.
  • Experience operating in ambiguous or emerging domains where processes, roles, governance, and success measures must be created rather than inherited.
  • Experience working with IT, product, analytics, or digital teams to transition capabilities from build/scaling into business adoption and ongoing operations.

Travel: No or very little travel likely

Work Conditions: Work primarily in a climate-controlled environment with minimal safety/health hazard potential.

Physical Demands Work primarily in a climate-controlled environment with minimal safety/health hazard potential.

This position is classified as "in-office." As an in-office role, it requires employees to work from a designated Carnival office in South Florida OR Seattle Monday through Thursday each week.

What You Can Expect

  • Cruise and Travel Privileges for You and Your Family
  • Health Benefits
  • 401(k)
  • Employee Stock Purchase Plan
  • Training & Professional Development
  • Tuition & Professional Certification Reimbursement
  • Base Salary Range : $89,600to $1

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