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Ai Operations Jobs in Texas (NOW HIRING)

Oremda Infotech Inc

AI Operations Analyst

Spring, TX · On-site

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.

WizeHire, Inc

Ai Operations Solutions Specialist

Austin, TX · On-site

$165 - $276/hr

AI Operations Solutions Specialist (AI Forward Deployed Engineer) Employment: Contract, 90-day Location: Preferred Hybrid in Austin, TX The Opportunity: Efinity Mortgage is a growing mortgage lending ...

New

Efinity Mortgage

Ai Solutions Architect

Austin, TX · On-site

$125/hr

AI Solutions Architect (AI Forward Deployed Engineer) Employment: Contract, 90-day Location ... Efinity Mortgage is a growing mortgage lending operation preparing to scale production without ...

Efinity Mortgage

Ai Solutions Architect

Austin, TX · On-site

$120 - $125/hr

AI Solutions Architect (AI Forward Deployed Engineer) Employment: Contract, 90-day Location ... Efinity Mortgage is a growing mortgage lending operation preparing to scale production without ...

New

MasterCard

Senior AI Platform Engineer (DevOps)

Austin, TX · On-site

$128K - $165K/yr

Title and Summary Senior AI Platform Engineer (DevOps) Who is Mastercard? Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, w ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 Software Engineer III - AI/ML Platform Operations - Remote (Open) Location Arizona - Home Teleworkers ...

Scotiabank

Director, AI Platform

Dallas, TX · On-site

AI Operations, Observability & Trust: • Establish and deliver an AI operations framework that enables reliable, measurable, and governed AI services in production. • Deliver platform capabilities ...

Scotiabank

Director, AI Platform

Dallas, TX · On-site

$180 - $240/hr

AI Operations, Observability & Trust * Establish and deliver an AI operations framework that enables reliable, measurable, and governed AI services in production. * Deliver platform capabilities for:

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Ai Operations information

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.

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

The most popular types of Ai Operations jobs in Texas are:

What are popular job titles related to Ai Operations jobs in Texas?

For Ai Operations jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Ai Operations jobs in Texas look for?

The top searched job categories for Ai Operations jobs in Texas are:

What cities in Texas are hiring for Ai Operations jobs?

Cities in Texas with the most Ai Operations job openings:

Ai Operations jobs near you
Infographic showing various Ai Operations job openings in Texas as of August 2026, with employment types broken down into 82% Full Time, 14% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution.

AI Operations Analyst

Oremda Infotech Inc

Spring, TX • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

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.

Instead, it appears focused on AI operational governance and portfolio support.

Desired exposure includes:

• AI application support

• Responsible AI concepts

• AI governance

• Data governance

• AI lifecycle management

• AI use case registration processes

Candidates do not necessarily need:

• Machine learning development

• Model training

• Data science expertise

• Advanced AI engineering experience

OIL and GAS is a PLUS


Automation / Reporting

• Basic Python

• Reporting automation

• Dashboard development

• Process automation

Red Flags / Gaps

Pure software developer with no operational ownership

Pure data scientist lacking application support experience

No enterprise application administration background

No governance/compliance/process experience

Very limited stakeholder-facing experience

Frequent short tenures without evidence of ownership

Apply