ZipRecruiter

Log In

1

Ai Data Labeling Jobs in Texas (NOW HIRING)

Socket.dev

Director, AI & Data Platforms

Austin, TX · On-site

$180 - $240/hr

Director, AI & Data Platforms Requisition ID: req1420 Employment Type: Unclassified Regular ... labeling, access controls and policy enforcement. * Ensure governance is implemented through ...

previous pagenext page

Showing results 21-40

All JobsAi Data Labeling JobsAi Data Labeling Jobs in Texas

Ai Data Labeling information

What is an AI data labeling?

An AI Data Labeling job involves annotating or tagging data (such as images, text, audio, or video) to train machine learning models. Labelers categorize, classify, or highlight data based on specific guidelines to help AI understand patterns and make accurate predictions. This process is crucial for supervised learning, where models learn from labeled examples. AI Data Labeling jobs are common in industries like healthcare, finance, and autonomous vehicles. Attention to detail and consistency are key skills for success in this role.

What does an AI data labeling do?

As an AI Data Labeling professional, your primary responsibilities include reviewing raw images, audio, or text data and accurately tagging or classifying them based on set guidelines provided by your employer. You may also be required to flag ambiguous cases or data anomalies and provide feedback to improve labeling instructions. Collaboration with data scientists or machine learning engineers is common to ensure your work aligns with project needs. Maintaining high accuracy while meeting productivity goals is essential for success in this role.

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

To thrive as an AI Data Labeling professional, you need strong attention to detail, analytical thinking, and the ability to follow precise guidelines, typically backed by a high school diploma or higher. Familiarity with annotation tools such as Labelbox, Supervisely, or internal labeling platforms, as well as basic understanding of data privacy practices, is often required. Patience, reliability, and good communication skills are important soft skills for consistently delivering high-quality labeled datasets and working effectively with team members. These skills ensure accurate data preparation for training AI models, directly impacting the model’s performance and the success of machine learning projects.

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

The most popular types of Ai Data Labeling jobs in Texas are:

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

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

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

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

What cities in Texas are hiring for Ai Data Labeling jobs?

Cities in Texas with the most Ai Data Labeling job openings:

Ai Data Labeling jobs near you
Infographic showing various Ai Data Labeling job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Director, AI & Data Platforms

Socket.dev

Austin, TX • On-site

$180 - $240/hr

Other

Posted 18 days ago

Job description

Director, AI & Data Platforms

Requisition ID: req1420

Employment Type: Unclassified Regular Full-Time (URF)

Division: Enterprise Data & Analytics

Compensation: Depends on Qualification

Job Closing: 8/23/2026

Location: TRS Headquarters Building 2
1900 Aldrich Street
Austin, Texas, 78723
United States

WHO WE ARE:

The Information Technology (IT) Division lays the foundation for TRS to deliver excellent service experiences across the organization and with our members. We serve with purpose through mentorship and collaboration across a broad variety of teams unified by innovation to create technology and information solutions that have a positive impact on our members’ lives.

We invite you to join one of Austin’s Top Workplaces. TRS offers a best-in-class combination of technology and continuous learning opportunities to equip you to solve problems, expand your knowledge, and create impact for 1 in 20 Texans.

The Director of AI & Data Platforms is responsible for leading the enterprise strategy, architecture, engineering, and operations of TRS’s artificial intelligence and data platforms. The incumbent will own the shared AI and data foundations that enable scalable, secure, and compliant analytics and AI capabilities across the organization, and ensure that platform capabilities, governance enforcement, and architecture standards are consistently applied to support business-driven data delivery and AI initiatives. This role is a key member of IT leadership and serves as the enterprise point of accountability for AI and data platform execution.

WHAT WILL YOU DO:Leadership
  • Builds and leads a high-performing team of platform engineers, architects, AI engineers, and governance specialists.
  • Develops workforce capabilities in AI and data platform engineering.
  • Partners with IT leadership on organizational strategy and staffing growth.
  • Directs department staff, directly and through team leaders, including hiring, directing, monitoring, evaluating, and motivating staff.
  • Establishes clear career paths and role specialization within AI and data platform domains.
  • Provides direction, monitors team work loads and work processes, and takes corrective actions as needed to ensure that all operations are covered, and productivity, customer service, and quality goals are met.
  • Ensures compliance with applicable federal, state, agency, and department policies, procedures, rules, and regulations.
  • Assesses training needs of team members and arranges for or provides training, coaching, and technical assistance.
Enterprise Enablement & Adoption
  • Serves as the enabling technology partner for Data Delivery and LOB teams.
  • Provides “paved roads” for AI and data delivery teams.
  • Supports developer experience, onboarding, and platform adoption.
  • Reduces duplication and tool sprawl across the enterprise.
  • Partners closely with Enterprise Technology Services to achieve enablement goals.
Enterprise AI & Data Platform Strategy, Architecture, and Governance
  • Defines and execute the strategy for enterprise AI and data platforms (e.g., Fabric, Databricks, Azure AI services).
  • Oversees platform architecture, engineering, and lifecycle management.
  • Ensures scalability, reliability, performance, and cost optimization (FinOps).
  • Establishes and maintains enterprise AI and data platform architecture standards.
  • Ensures the platform provides the infrastructure and tooling to support AI-ready data patterns (e.g., semantic layers, RAG, data integration patterns).
  • Drive consistency in interoperability and platform alignment.
  • Owns platform architecture across the AI and data estate; sets architectural direction for how AI capabilities are built, deployed, and governed on shared infrastructure.
  • Owns enterprise data governance tooling and enforcement mechanisms, including data catalog (Purview or equivalent), data classification and sensitivity labeling, access controls and policy enforcement.
  • Ensure governance is implemented through platform capabilities, not manual processes.
  • Partner with enterprise governance bodies to align policy with technical enforcement.
Platform Engineering, Operations, and Enablement
  • Leads platform operations including monitoring, incident management, and reliability.
  • Owns environment strategy (sandbox, development, testing, production).
  • Establishes DevOps practices including CI/CD, version control, and deployment standards.
  • Ensures secure, compliant, and auditable platform usage.
  • Leads development of reusable AI capabilities (e.g., agents, copilots, orchestration frameworks).
  • Supports AI experimentation, R&D, and transition to production-ready capabilities.
  • Delivers shared services and patterns that enable downstream delivery teams.

Performs related work as assigned.

WHAT WILL YOU BRINGRequired Education
  • Bachelor’s degree from an accredited college or university in Computer Science, Information Systems, Engineering, or a closely related field.
  • High school diploma or equivalent and additional full-time experience in data platforms, cloud architecture, IT enterprise or related experience may be substituted on an equivalent year-for-year basis.
Required Experience
  • Eight (8) years of full-time directly related, progressively responsible experience in data platforms, cloud architecture, IT enterprise or related experience.
  • Four (4) years of experience leading, or supervising the work of others, required.
  • Experience with enterprise AI platforms and agentic frameworks (e.g., Azure AI Foundry, Azure OpenAI Service, Copilot Studio, Databricks Model Serving).
  • Experience in enterprise AI adoption practices through agentic frameworks (LangChain, Semantic Kernel/Microsoft Agent Framework, Azure AI Agent Service), RAG pipeline design, MCP integrations, prompt engineering and responsible AI frameworks, AI guardrails and content safety.
  • A master’s degree or doctoral degree in a closely related field may be substituted on an equivalent year-for-year basis.
Required Registration, Certification, or Licensure
  • None.
Knowledge, Skills, and AbilitiesKnowledge of:
  • Data governance, security, and compliance frameworks.
  • Modern data platforms (e.g., Databricks, Azure, Fabric, Snowflake).
  • People leadership in the data platform, data engineering and data operations space.
  • A diverse base of knowledge that allows you to help your team solve complex technical problems.
  • The principles, practices, and techniques of computer programming and systems analysis and design; all phases of software development and project management; and computing standards and development methodologies, including Systems Development Life Cycle methodologies.
  • Varying technological architectures, security, and technology trends.
  • Agency computing standards, security, and development methodologies.
Skills in:
  • Leading large-scale data and AI platform initiatives
  • Multi-agent orchestration patterns (sequential, concurrent, handoff) and agent governance/observability tooling.
  • Leading analytics project teams; and organizing, managing, and motivating staff to meet project goals and objectives.
  • Analyzing problems and devising innovative and effective solutions, including collecting and analyzing complex data, evaluating information and business processes, and drawing logical conclusions.
  • Designing complex computer programs.
  • Project planning and management; planning, organizing, and coordinating work assignments to effectively meet frequent and/or multiple deadlines; handling multiple tasks simultaneously; and managing conflicting priorities and demands.
  • Communicating complex technical information to people of varying technical backgrounds.
Ability to:
  • Establish and maintain harmonious working relationships with co-workers, agency staff, and external contacts.
  • Work effectively in a professional team environment.
  • Plan strategically and align with peers in complex technical and operating environments.
Military Occupational Specialty (MOS) Codes:

Veterans, Reservists or Guardsmen with experience in the Military Occupational Specialty ( https://www.trs.texas.gov/files/trs-military-crosswalk.xlsx ) along with the minimum qualifications listed above may meet the minimum requirements and are highly encouraged to apply. Please contact Talent Acquisition at careers@trs.texas.gov with questions or for additional information.

To view all job vacancies, visit www.trs.texas.gov/careers or www.trs.csod.com/careersite.

For more information, visit www.trs.texas.gov.

#J-18808-Ljbffr

Apply