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Jobs · Engineering · Oklahoma

AI Security Engineer Manager

Deloitte · Tulsa, OK · 3 days ago
HybridEngineering$119k–$244k/yrFull-time

About the role

This role plays a critical role in securing the development and deployment of AI/ML and Generative AI solutions. The position requires a collaborative, execution-focused leader who can influence teams, mentor engineers, and ensure AI systems meet enterprise security, risk, and compliance expectations.

Responsibilities

  • Secure, Outcome-Driven Delivery: Design and deliver AI-enabled solutions that are secure by design, balancing business value with risk mitigation. Solve complex problems while ensuring protection of data, models, and systems.

  • Hands-On AI Security Engineering: Actively contribute to architecture, design, and development of AI/ML and GenAI systems with embedded security controls. Integrate security across the SSDLC, including code reviews, testing, and deployment.

  • AI Risk Identification and Mitigation: Identify and address AI-specific vulnerabilities, including prompt injection, data leakage, model manipulation, and misuse. Implement practical safeguards to ensure system integrity and trustworthiness.

  • Technical Leadership and Advocacy: Serve as a trusted technical voice for secure AI engineering. Ensure solutions are feasible, secure, and aligned with business and customer objectives.

  • Engineering Excellence with Security Focus: Maintain high standards for code quality, scalability, and security. Contribute to secure coding practices, reusable patterns, and continuous improvement across engineering teams.

  • Iterative and Responsible Innovation: Support rapid experimentation while applying appropriate security guardrails. Enable teams to innovate safely through controlled, risk-aware development practices.

  • Cross-Functional Collaboration: Partner closely with product, engineering, cybersecurity, and risk teams to embed AI security into solutions. Balance usability, performance, and security in decision-making.

  • Standards and Best Practices: Apply and help evolve standards for AI security, including data protection, access control, model validation, and monitoring within DevSecOps and MLOps pipelines.

  • Communication and Influence: Clearly articulate technical risks, trade-offs, and solutions to both technical and non-technical stakeholders. Contribute to alignment and informed decision-making.

Requirements

  • Bachelor’s degree or equivalent in Computer Science, Computer Engineering, Business Administration

  • Minimum 6 years of relevant experience in software engineering, cybersecurity, and/or including AI/ML, with hands-on delivery experience

  • Minimum 1 year of people and/or process management experience

Qualifications

  • Strong understanding of AI/GenAI technologies and associated security risks (e.g., prompt injection, data exposure, adversarial threats)

  • Experience building and securing applications using Python, JavaScript, or similar, along with ML frameworks (e.g., PyTorch, TensorFlow)

  • Familiarity with secure development practices (DevSecOps) and integrating security into CI/CD and MLOps pipelines

  • Experience with cloud platforms (AWS, Azure, GCP) and cloud-native security principles

  • Knowledge of data protection, identity/access management, and secure architecture patterns

  • Ability to work across teams, mentor engineers, and contribute to a strong engineering culture

  • Strong communication skills with the ability to translate technical concepts into business-relevant insights

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