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Senior Artificial Intelligence Testing Jobs in Texas

Senior AI & Machine Learning Engineer

San Antonio, TX ยท On-site

$143K - $273K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Opportunity The Senior Artificial Intelligence and Machine Learning Engineer will be part of a ... testing, deployment, scheduling, application integration, production support, API development, and ...

Senior AI & Machine Learning Engineer

San Antonio, TX ยท On-site +1

$143K - $273K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Opportunity The Senior Artificial Intelligence and Machine Learning Engineer will be part of a ... testing, deployment, scheduling, application integration, production support, API development, and ...

USA_Artificial Intelligence Engineer

Frisco, TX ยท On-site

$114K - $151K/yr

Bellevue, WA (Hybrid - 3 days/week) or Remote Role Overview We're building a new product in the real estate tech space and are looking for a Senior AI Engineer to join our founding AI team. You'll ...

Artificial Intelligence Agent Engineer

San Antonio, TX ยท On-site

$71K - $95K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Plans and executes versioning, testing, and rollout strategies (unit, integration, regression, UX). * Maintains agent knowledge interfaces and schedules corpus refresh, drift detection, and policy ...

Showing results 21-40

Senior Artificial Intelligence Testing information

What is a senior artificial intelligence testing professional?

Senior Artificial Intelligence Testing professionals are experienced specialists responsible for designing, executing, and overseeing tests to ensure the quality, reliability, and ethical standards of AI systems. They develop test plans, create testing frameworks, and analyze AI model behaviors to identify errors, biases, or security vulnerabilities. They often collaborate with data scientists, engineers, and product managers to refine AI algorithms and ensure they perform as intended in real-world scenarios. Their role is critical in maintaining trust and safety in AI-driven products and services.

What skills and qualifications are needed to thrive as a senior artificial intelligence testing professional?

To thrive as a Senior Artificial Intelligence Testing professional, you need expertise in software testing methodologies, machine learning concepts, and proficiency in programming languages like Python, along with a degree in computer science or a related field. Familiarity with AI testing frameworks, automated testing tools (such as TensorFlow, PyTorch, Selenium), and relevant certifications (like ISTQB) is often required. Strong analytical thinking, attention to detail, and effective communication skills distinguish top performers in this role. These competencies are critical to ensuring the quality, reliability, and ethical integrity of AI systems in complex, real-world applications.

What are common challenges faced by senior artificial intelligence testing professionals, and how can they be addressed?

Senior Artificial Intelligence Testing professionals often encounter challenges such as ensuring the reliability of complex AI models, dealing with insufficient or biased data, and validating unpredictable outputs. Addressing these issues typically involves developing comprehensive test plans, employing advanced testing frameworks, and collaborating closely with data scientists and engineers. Regular communication with cross-functional teams and staying updated on the latest AI testing methodologies are also essential for overcoming these challenges and ensuring robust, ethical AI systems.

What is the difference between Senior Artificial Intelligence Testing vs Machine Learning Engineer?

AspectSenior Artificial Intelligence TestingMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, experience in AI testing toolsBachelor's or Master's in CS, strong programming skills, knowledge of ML frameworks
Work EnvironmentAI development teams, quality assurance, testing labsData science teams, software development environments, cloud platforms
Employer & Industry UsageTech companies, AI-focused firms, research institutionsTech companies, startups, research labs, AI product companies
Common Search & Comparison IntentUnderstanding testing roles in AI projectsDeveloping and deploying machine learning models

While Senior Artificial Intelligence Testing focuses on evaluating and validating AI systems for accuracy and reliability, Machine Learning Engineers design, build, and optimize machine learning models. Both roles require a strong background in computer science and AI, but their core responsibilities differ: testing emphasizes quality assurance, whereas engineering emphasizes model development and deployment.

How do I become a senior artificial intelligence testing?

To become a senior artificial intelligence testing professional, candidates typically need a strong background in computer science, machine learning, or related fields, along with experience in AI development and testing. Proficiency in programming languages like Python, knowledge of AI frameworks, and familiarity with testing tools are essential, often complemented by advanced degrees or certifications in AI or software testing. Progression usually involves gaining experience in AI projects, demonstrating leadership skills, and staying updated with emerging AI technologies and testing methodologies.

Is senior artificial intelligence testing a good career?

Senior artificial intelligence testing is a specialized role that involves evaluating AI systems for accuracy, reliability, and safety, often requiring skills in programming, data analysis, and understanding of machine learning models. It is a growing field with increasing demand as AI technologies expand across industries, offering opportunities for career advancement and specialization. The role typically requires experience, technical certifications, and knowledge of testing tools and frameworks.

What cities in Texas are hiring for Senior Artificial Intelligence Testing jobs?

Cities in Texas with the most Senior Artificial Intelligence Testing job openings:

Artificial Intelligence Security Architect, Director (Irving)

Citibank (Switzerland) AG

Irving, TX โ€ข On-site

$62.50 - $80.75/hr

Full-time

Posted 2 days ago

New


Job description

## Artificial Intelligence Security Architect, DirectorApplyremote type: Hybridlocations: Irving Texas United States: Tampa Florida United Statestime type: Full timeposted on: Posted Yesterdaytime left to apply: End Date: June 22, 2026 (5 days left to apply)job requisition id: 26944133Citi, the leading global bank, has approximately 200 million customer accounts and does business in more than 160 countries and jurisdictions. Citi provides consumers, corporations, governments, and institutions with a broad range of financial products and services, including consumer banking and credit, corporate and investment banking, securities brokerage, transaction services, and wealth management.As a bank with a brain and a soul, Citi creates economic value that is systemically responsible and in our clientsโ€™ best interests. As a financial institution that touches every region of the world and every sector that shapes your daily life, our Enterprise Operations & Technology teams are charged with a mission that rivals any large tech company. Our technology solutions are the foundations of everything we do from keeping the bank safe, managing global resources, and providing the technical tools our workers need to be successful to designing our digital architecture and ensuring our platforms provide a first-class customer experience. We reimagine client and partner experiences to deliver excellence through secure, reliable, and efficient services.Our commitment to diversity includes a workforce that represents the clients we serve from all walks of life, backgrounds, and origins. We foster an environment where the best people want to work. We value and demand respect for others, promote individuals based on merit, and ensure opportunities for personal development are widely available to all. Ideal candidates are innovators with well-rounded backgrounds who bring their authentic selves to work and complement our culture of delivering results with pride. If you are a problem solver who seeks passion in your work, come join us. Weโ€™ll enable growth and progress together.About Our Team:The Chief Information Security Office (CISO) is home to deeply talented colleagues that work to ensure the safety of Citi's clients', our revenue, our employees and our proprietary data. We manage information security as one end-to end program โ€“ one with a clear mandate and accountability. Our mission is a program that is fully anchored to modern control and architectural frameworks, is fully aligned with the enterprise architecture of the firm and is deeply integrated into the sectors and functions.Position Overview:The Enterprise Security Architect for Artificial Intelligence (AI) is a senior individual contributor position responsible for defining the strategic direction and designing secure architectures for Citiโ€™s enterprise IAM program and the secure adoption, development, and deployment of advanced AI/ML technologies, including agentic AI systems. This role involves developing robust security policies, guiding secure architecture across various IAM systems, and ensuring the comprehensive security and trustworthiness of AI/ML platforms and applications, from data ingestion to model deployment and operational monitoring.The architect will specifically focus on securing the lifecycle of AI, including mitigating risks associated with agentic AI's autonomous decision-making, multi-agent interactions, and continuous learning capabilities. This role requires deep expertise in AI security, ethical AI principles, and compliance with evolving regulatory standards. The architect will collaborate with cross-functional teams, mentor security professionals, and drive innovation in security testing, AI model validation, and governance. Strong leadership, strategic planning, and a deep understanding of emerging threats, risk management, and the unique security challenges presented by advanced IAM and AI paradigms are essential.Responsibilities:* Leadership + Partner, coach and functionally lead IT, engineering, development, data science, and business teams through collaborative design discussions focused on IAM and comprehensive AI security, including agentic systems. + Educate internal and external clients on security risk, best practices, and the secure, ethical implementation of IAM and AI.* Vision and Strategy + Define and lead the security strategy for enterprise-wide Identity and Access Management, including identity lifecycle, authentication, authorization, privileged access management, and directory services, with a focus on Zero Trust principles and regulatory alignment. + Establish and evolve the comprehensive security strategy and architectural guidelines for all AI/ML initiatives, ensuring the secure and ethical design, development, deployment, and operation of AI systems, models, and data. This includes specific considerations for securing agentic AI architectures, their interaction protocols, decision-making integrity, and control mechanisms. + Develop strategies for AI risk management, addressing concerns related to data privacy, model bias, explainability, adversarial attacks, and the secure integration of AI into critical business processes.* Architecture and Innovation + Develop and maintain IAM reference architectures, playbooks, and control frameworks tailored to the bankโ€™s technology stack, third-party oversight obligations, and global regulatory landscape. + Architect secure, scalable, and resilient IAM solutions for workforce, customer, and partner identities, encompassing identity federation, single sign-on (SSO), multi-factor authentication (MFA), privileged access management (PAM), and robust access governance across diverse environments. + Develop and maintain advanced AI security reference architectures, trust frameworks, and best practices for securing the entire AI/ML lifecycle. This includes: - Data Security: Ensuring the integrity, confidentiality, and provenance of training and inference data. - Model Security: Protecting models from adversarial attacks (e.g., evasion, poisoning), ensuring model integrity, interpretability, and robustness. - Platform Security: Securing AI/ML development and deployment platforms (e.g., MLOps pipelines, data science environments). - Agentic AI Security: Architecting security for autonomous AI agents, including secure communication between agents, trustworthy decision-making frameworks, verifiable audit trails for agent actions, and mechanisms to prevent unintended or malicious behavior in multi-agent systems. + Partner with engineering, platform operations, data science, and enterprise architecture teams to embed IAM security and comprehensive AI security throughout service lifecycles โ€” from ideation through production.* Engineering and Integration + Integrate advanced security controls into IAM platforms and AI/ML development, deployment, and operational workflows (e.g., MLOps), driving secure-by-design principles for identities, access, data, and AI systems. + Automate security testing, policy enforcement, and compliance checks within IAM provisioning, access governance processes, and AI model development and deployment pipelines. + Implement security measures for monitoring and controlling agentic AI behavior, including anomaly detection for agent actions, secure orchestration of agent workflows, and ensuring auditable decision processes.* Governance and Compliance + Ensure compliance with banking regulations including GLBA, SOX, FFIEC, PCI-DSS, NYDFS, OCC cybersecurity guidelines, GDPR, CCPA, and emerging AI regulations (e.g., EU AI Act, NIST AI Risk Management Framework). Integrate security architecture into audit and regulatory programs for both IAM and AI. + Establish robust governance frameworks for identity management, access controls, and AI risk management, including ethical AI considerations, bias detection and mitigation, data lineage, explainable AI (XAI), and accountability frameworks for AI systems, particularly autonomous agents.Qualifications:* 15+ years of experience in cybersecurity, with 5+ years in enterprise security architecture focused on comprehensive Artificial Intelligence security.* Demonstrated success leading security architecture for financial services, banks, or other highly regulated industries.* Technical expertise in enterprise IAM solutions (e.g., Okta, Azure AD, Ping Identity, SailPoint, CyberArk), identity protocols (e.g., OAuth, OpenID Connect, SAML, SCIM), directory services, and advanced access governance.* Strong command of AI/ML concepts, MLOps practices, data science platforms, and extensive experience in securing the entire AI/ML lifecycle, including:* Data security (data at rest, in transit, and in use within AI systems).* Model security (adversarial machine learning, model poisoning, model extraction, integrity validation).* Secure development and deployment of AI models and applications.* Specific experience with agentic AI systems, multi-agent architectures, and securing their autonomy, interactions, and decision-making processes.* In-depth knowledge of AI ethics, fairness, transparency, and explainability principles and their practical application in security architecture.* Experience with regulatory audits and control frameworks (e.g., NIST 800-53, ISO 27001, FFIEC CAT, NIST AI RMF), specifically as they apply to IAM and AI.* Proven leadership in cross-functional teams, architecture review boards, and strategic planning sessions.* Excellent communication and presentation skills, with the ability to engage both technical and executive audiences.* Preferred certifications: CISSP, CISM, Certified Identity and Access Manager (CIAM), Certified Data Privacy Solutions Engineer (CDPSE), AWS/Azure/GCP Security certifications (with an emphasis on identity, data, and AI services), relevant AI/ML security certifications (e.g