Scientist, AI & Cloud Security Architect

L3Harris is dedicated to recruiting and developing high-performing talent who are passionate about what they do. Our employees are unified in a shared dedication to our customers’ mission and quest for professional growth. L3Harris provides an inclusive, engaging environment designed to empower employees and promote work-life success. Fundamental to our culture is an unwavering focus on values, dedication to our communities, and commitment to excellence in everything we do.

L3Harris is the Trusted Disruptor in defense tech. With customers’ mission-critical needs always in mind, our employees deliver end-to-end technology solutions connecting the space, air, land, sea and cyber domains in the interest of national security.

Job Title: Scientist, AI & Cloud Security Architect

Job Code: 40743

Job Location: (On Site) Melbourne, FL; Salt Lake City, UT; Greenville, TX; Plano, TX; Rockwall, TX; Clifton, NJ; Rochester, NY

Job Schedule: Employees work 9 out of every 14 days – totaling 80 hours worked – and have every other Friday off

The Scientist is responsible for defining and driving the enterprise security strategy, target-state architecture, and governance model for AI, cloud and container platforms across Azure and AWS. Reporting within the CISO organization, this role focuses on secure-by-design architecture, enterprise guardrails, risk-informed adoption patterns, and security integration for modern platforms.

This leader partners closely with Security Architecture, Enterprise Architecture, Infrastructure and Data/AI teams to establish secure, scalable, and reusable platform patterns that enable rapid, compliant adoption of AI and cloud capabilities across the enterprise. The role serves as a strategic bridge between cybersecurity, enterprise technology, and engineering organizations to ensure AI, cloud, and container platform innovation is enabled with strong security, resilience, and governance foundations.

• Develop enterprise AI security and governance frameworks covering model lifecycle, data boundaries, and risk controls.

• Create AI reference architectures ensuring secure, compliant integration of generative and cloud-native AI capabilities.

• Advise leadership on emerging AI technologies, associated risks, and secure platform adoption strategies.

• Define multi-cloud security strategy, reference architectures, and enterprise guardrails for Azure, AWS, and hybrid environments.

• Standardize observability, networking, and compliance architectures across cloud platforms.

• Lead design reviews and maintain cloud architectural patterns enabling secure-by-design adoption.

• Partner with software engineering teams to embed security guardrails into their active implementations.

Container Platform Security

• Define security architecture, controls, and governance for Kubernetes, container orchestration, and runtime environments.

• Establish secure build, registry, and deployment patterns for containers across cloud and on‑prem platforms.

• Integrate container security posture, registry/image scanning, host OS scanning, and workload protection into enterprise standards.

Collaboration

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