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Ai Labelling Jobs in Texas (NOW HIRING)

Product and Labeling Inspector

Houston, TX · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

The Product and Labeling Inspector ensures product integrity, labeling accuracy, and regulatory ... Utilize AI-supported document analysis tools to improve review accuracy, efficiency, and ...

Product and Labeling Inspector

Houston, TX · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

POSITION SUMMARY The Product and Labeling Inspector ensures product integrity, labeling accuracy ... Utilize AI-supported document analysis tools to improve review accuracy, efficiency, and ...

New

Partner with the platform team to define the storage-fault predictor: which signals, which labels ... Strong understanding of AI training I/O patterns: checkpoint frequency, dataset loading, shuffle ...

Senior Applied AI Engineer

Austin, TX · On-site

$103K - $142K/yr

The Senior Applied AI Engineer will design and build agentic systems, automate workflows, and ... , labeling and ops loops, support triage, internal copilots) and partner with the SMEs running ...

AI Research Scientist- Associate Director

Dallas, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Design and implement processes to perform for AI model training; from infrastructure, to data labelling, evaluations, among other areas; work to ensure models can be deployed and managed in ...

AI Solutions Specialist

Dallas, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

Working knowledge of identity, access control, and data governance controls within Microsoft 365, including sensitivity labels, DLP, and permission scoping, and how these impact AI-driven solutions.

AI Solutions Specialist

Dallas, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

Working knowledge of identity, access control, and data governance controls within Microsoft 365, including sensitivity labels, DLP, and permission scoping, and how these impact AI-driven solutions.

Working knowledge of identity, access control, and data governance controls within Microsoft 365, including sensitivity labels, DLP, and permission scoping, and how these impact AI-driven solutions.

Showing results 21-40

Ai Labelling information

What are some typical challenges faced in AI labelling roles and how can they be managed?

One common challenge in AI Labelling roles is maintaining accuracy and consistency when labeling large volumes of data according to detailed guidelines, which can become repetitive or mentally taxing. Managing these challenges often involves taking regular breaks, double-checking work, and staying up-to-date with any updates to annotation standards provided by the team. Collaborating with supervisors and peers to clarify uncertainties and seek feedback also helps ensure high-quality output. Over time, professionals in this role often develop efficient workflows and a keen eye for detail, opening doors to advancement into quality assurance or project coordination positions within the data annotation field.

What is an AI labelling?

An AI labelling job involves annotating data—such as images, text, audio, or video—to help train machine learning models. This process includes tasks like tagging objects in images, transcribing speech, or categorizing text. The labelled data is crucial for AI systems to learn and make accurate predictions. These jobs are commonly found in industries like tech, healthcare, and autonomous driving. Attention to detail and consistency are key skills for this role.

What are the key skills and qualifications needed to thrive in AI labelling?

To thrive in an AI Labelling role, you need attention to detail, basic data analysis skills, and the ability to follow complex guidelines, with many roles requiring at least a high school diploma or equivalent. Familiarity with data annotation tools, image or text labeling platforms, and sometimes basic scripting or database systems is beneficial. Strong communication, time management, and the ability to work both independently and as part of a team are valuable soft skills. These competencies ensure the consistent and accurate labeling of data, which is critical for training high-quality AI and machine learning models.

What cities in Texas are hiring for Ai Labelling jobs?

Cities in Texas with the most Ai Labelling job openings:

Infographic showing various Ai Labelling job openings in Texas as of August 2026, with employment types broken down into 73% Full Time, 23% Part Time, and 4% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution.

Senior AI Security Architect

Cognizant Technology Solutions

Fort Worth, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago


Cognizant rating

7.4

Company rating: 7.4 out of 10

Based on 85 frontline employees who took The Breakroom Quiz

52nd of 72 rated business consultants


Job description

Practice - CIS - Cloud, Infrastructure, and Security Services
About Cloud Infrastructure & Security Services: Cognizant's Cloud, Infrastructure, and Security Services Practice (CIS), is all about embracing digital transformation by driving core modernization holistically across layers. We help customers transform infrastructure and workplace to meet the rapidly evolving needs of the digital era. Our holistic approach delivers key results for our customers by achieving cloud driven modernization and workplace and operational transformation to run the business in a secure environment.
Job Summary
This role is responsible for end-to-end security architecture for an enterprise Agentic AI platform and lead the data security strategy for AI. This senior role combines two critical responsibilities: Agentic AI Security Architecture and Data Security Posture Management (DSPM). The successful candidate will be accountable for designing a secure AI platform while protecting and governing the data that flows through AI agents and services.
*Please note, this role is not able to offer visa transfer or sponsorship now or in the future*
In this role, you will:
• Define, develop, and own the Agentic AI Reference Security Architecture, including Platform 1.0 security hardening and future roadmap enhancements.
• Implement, operationalize, and manage Microsoft Purview DSPM for AI, leveraging Microsoft FastTrack services where appropriate.
• Establish and maintain enterprise sensitivity labeling and machine learning-based auto-classification standards for AI-related data.
• Map, monitor, and govern data flows into and out of AI agents and AI-enabled workloads.
• Define security architecture standards for agent-to-API and agent-to-data access patterns.
• Design and secure Agentic AI solutions across a multi-cloud environment, including Azure and AWS, ensuring consistent security controls regardless of deployment location.
• Collaborate closely with Identity, Application Security (AppSec), and Governance, Risk, and Compliance (GRC) teams to ensure security controls are embedded into solutions from the design stage.
What you need to have to be considered
• Deep expertise in Azure and Microsoft 365 security architecture, including Microsoft Sentinel, Microsoft Entra ID, and Microsoft Defender for Cloud.
• Proven experience designing and securing Agentic AI and Generative AI platforms in enterprise environments.
• Hands-on experience securing multi-cloud environments across Azure and AWS, including AWS Bedrock Agents, Lambda, and IAM.
• Strong expertise in Microsoft Purview, including DSPM for AI, sensitivity labeling, data flow mapping, information protection, and ML-based auto-classification.
• Strong understanding of AI security, API security, agent-to-agent, agent-to-API, and agent-to-data access patterns.
• Familiarity with Microsoft Copilot Studio and enterprise AI agent platforms.
• Experience implementing Zero Trust principles, identity security controls, and secure-by-design architectures.
• Proven track record of designing enterprise-scale security solutions within regulated environments.
• Strong knowledge of data governance, data protection, privacy, and compliance requirements for AI-enabled solutions.
• Excellent stakeholder management skills with the ability to partner effectively with Identity, AppSec, Engineering, and GRC teams.
Preferred Qualifications
• Experience within life sciences, healthcare, medical devices, pharmaceutical, or other regulated industries.
• Relevant certifications such as CISSP, SC-100, AZ-500, CCSP, or equivalent security certifications.
• Experience leading enterprise AI security, cloud security, or data protection initiatives at scale.
#LI-EF1
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Applications will be accepted until 16 Aug 2026.
Salary and Other Compensation:
The annual salary for this position is between $[160,000 - 185,000] depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan
About Cognizant:
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization's unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.
Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] for roles based in the Americas or [email protected] for roles based in India.

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