Overview
Skills
Job Details
Overview: This role supports the Product Security team with a focus on securing AI-driven applications, including Traditional ML, Generative AI, and Agentic AI systems. The position is ideal for a junior to mid-level security professional with a strong cybersecurity foundation and growing experience in AI/ML technologies.
Responsibilities
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Collaborate with product teams to embed security into AI/ML models, pipelines, and applications throughout the SDLC.
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Conduct security reviews for AI systems, including LLMs, generative models, and data pipelines.
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Support the development of AI security policies, standards, and controls aligned with NIST, ISO, and emerging AI regulations.
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Define and implement AI-specific risk controls, including model validation, bias mitigation, and explainability.
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Collaborate with legal, compliance, and data privacy teams to ensure adherence to evolving AI regulations.
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Assist in evaluating and implementing AI security tools for observability, model scanning, and data protection.
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Help build awareness and training materials for secure AI development practices across agile teams.
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Perform all other duties and projects as assigned.
Qualifications
Required Experience
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Bachelor’s degree in Computer Science, Information Security, or a related field.
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2+ years of experience in cybersecurity, with exposure to AI/ML technologies.
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Familiarity with secure coding practices, threat modeling, and cloud-native environments.
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Understanding of AI/ML concepts such as model training, inference, data labeling, and adversarial attacks.
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Knowledge of common AI risks (prompt injection, data poisoning, model misuse, etc.) and core cybersecurity concepts including authentication, encryption, and network security.
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Strong communication and collaboration skills in agile environments (SAFe experience a plus).
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Strong analytical skills to assess risks and vulnerabilities in complex systems.
Preferred Qualifications
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Professional certifications such as CCSK, CEH, or AI-specific credentials.
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Experience with Microsoft AI security tools including MS Defender for Cloud, MS Defender for Cloud Apps, Azure AI Content Safety, and MS Purview.
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Experience with AI security tools such as Zenity or HiddenLayer.
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Exposure to Power Platform, Power BI, or other low-code tools, including experience implementing data governance or DLP.
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Experience specifically in AI security or ML model governance.
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Proficiency in scripting and automation for security testing.
About the Client
The client is one of the largest investor-owned utility organizations in the United States, serving millions of customers through high-performing regulated utilities. The organization is committed to long-term, sustainable value creation, grid modernization, infrastructure investment, and innovation in energy technology. The client is actively advancing a cleaner energy future with a goal of achieving net-zero carbon emissions by 2050 while maintaining reliability and affordability. The organization also prioritizes community impact, diversity, and support for future generations.
#INDGEN #ZR