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# Cloud Artificial Intelligence Security Lead

- **Company:** Kforce Inc.
- **Location:** Tampa, FL, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Software System Penetration Testing, Computer Vision, Microsoft Azure, Cloud Computing, Cyber Security, Computer Engineering, Data Governance, Data Loss, Machine Learning, Meta-Data Management, Natural Language Processing, Tensorflow, Azure Machine Learning, Software Vulnerability Management, Azure Data Factory, Pytorch, Large Language Models, Deep Learning, AI Platforms, Information Technology, Machine Learning Operations
- **Published:** September 3, 2026
- **Apply:** https://www.dice.com/job-detail/3bd9d739-f912-48cf-8257-ede517ceeffc

## About the Role

* Bachelor's degree in Computer Science, Electrical or Computer Engineering, Statistics,
Econometrics, or related field, or equivalent work experience

 * 10+ years of hands-on experience in cybersecurity or information security
 * 4+ years of experience with Natural Language Processing (NLP) and Large Language
Models (LLM) desired

 * 4+ years of experience working in Microsoft Azure cloud environments (e.g. Azure Cloud
Services, Azure Fabric, Azure Data Factory, Purview Data Governance), as well as Azure AI services, as well as data cataloging practices

 * Familiarity with AI testing frameworks and tools such as TensorFlow, PyTorch, or Kerns
 * Deep understanding of Machine Learning lifecycles and MLOps
 * Deep understanding of the security challenges and controls for Large Language Models
(LLMs), including prompt injections, data poisoning, and model theft

 * Demonstrated proficiency with AI/ML fundamental concepts and technologies including ML,
deep learning, NLP, and computer vision

 * Experience assessing AI systems for ethical considerations and potential biases to make
sure they follow ethical standards and encourage inclusivity and diversity

Preferred Qualifications:

 * Master's degree in Computer Science, Electrical or Computer Engineering, Statistics,
Econometrics, or related field, or equivalent work experience

 * 12+ years of hands-on experience in cybersecurity or information security.

## Description

Kforce has a client in Tampa, FL that is seeking a Cloud Artificial Intelligence Security Lead., * Define and implement operational procedures for data cataloging, lineage, governance, and data protection to ensure AI solutions are secure, compliant, and aligned with organizational policies

 * Develop policy-driven security controls to protect AI, ML, and cloud-based solutions from data loss and unauthorized access
 * Partner with Data Scientists, GenAI Engineers, Developers, MLOps, and Data Governance teams to identify vulnerabilities, implement security best practices, and ensure compliance with standards such as NIST, SOC 2, and applicable regulations
 * Lead security assessments, penetration testing, vulnerability management, threat modeling, and risk mitigation activities for AI platforms and applications
 * Serve as the AI security SME throughout the design, development, deployment, and operation of AI/ML solutions, with a focus on protecting sensitive and personally identifiable information (PII)
 * Establish, document, and deliver AI security standards, procedures, training, and awareness programs across the organization
 * Develop and execute security testing strategies for GenAI and AI systems, including validation of confidentiality, integrity, availability, prompt injection resistance, and model security controls
 * Collaborate with QA and engineering teams to define test objectives, develop automated security testing, document results, and remediate identified defects or vulnerabilities
 * Design and implement security controls, detections, guardrails, and monitoring capabilities that improve the security, reliability, and resilience of AI solutions
 * Evaluate and secure AI/ML tools, platforms, libraries, and services while maintaining compliance with enterprise security standards
 * Support Enterprise Risk Management efforts by assessing AI systems for ethical risks, bias, fairness, transparency, and responsible AI practices


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