Senior AI Information Security Engineer

Corporate:

Light & Wonder’s corporate team is comprised of incredible talent that works across the enterprise, defying boundaries to provide essential services in an extraordinary manner to ensure the success of the organization and the well-being of employees.

Position Summary

The Senior AI Engineer will lead the design, development, and deployment of agentic AI systems and secure AI capabilities across the enterprise. Reporting to the Global CISO, this role owns hands-on development of AI agents, automation pipelines, and LLM-based workflows while ensuring they meet security, compliance, and governance requirements. The engineer will partner with Information Security, Legal, Compliance, Privacy, IT, and Engineering to take AI use cases from concept to production.

Key Responsibilities:

Agentic AI Development

• Design, build, and own production-grade agentic AI systems — including multi-step agents, tool-using LLM pipelines, retrieval-augmented generation (RAG) workflows, and automated decision-making systems.

• Develop and maintain the company’s internal agentic AI platform, including agent orchestration, memory management, tool integrations, and human-in-the-loop review workflows.

• Identify high-value agentic use cases across business functions and deliver working solutions end-to-end, from requirements through deployment and monitoring.

• Establish guardrails, safety patterns, and evaluation frameworks for agentic systems, including output validation, escalation logic, and auditability.

AI Security Engineering

• Implement and maintain security controls for AI tools and workflows: data handling, access controls, logging, monitoring, prompt injection mitigations, and acceptable-use enforcement.

• Perform security reviews and threat modeling for LLM integrations, agentic workflows, APIs, and third-party AI/SaaS solutions.

• Identify and mitigate AI-specific risks: sensitive data exposure, over-permissioned agents, insecure tool use, supply-chain exposure, and inadequate human oversight.

• Support AI governance and compliance activities with technical guidance, architecture input, and implementation evidence.

Security Engineering & Automation

• Develop scripts, integrations, and lightweight applications using Python, PowerShell, REST APIs, and workflow automation platforms.

• Build and maintain SIEM detections, SOAR playbooks, dashboards, and reporting capabilities, including telemetry for AI-enabled workflows.

• Engineer security improvements across identity, cloud, SaaS, endpoint, and data protection domains.

• Respond to security incidents involving AI tools, data exposure, and automation failures.

Collaboration & Governance

• Translate business and control objectives into secure AI designs, prototypes, and production capabilities.

• Manage and communicate project status, risk decisions, and implementation progress to stakeholders.

• Maintain standard operating documentation for knowledge transfer, audit readiness, and disaster recovery.

Qualifications

Technical Competencies

Required

• Agentic AI development: agent frameworks (e.g., LangChain, AutoGen, CrewAI), LLM APIs, tool use, RAG, vector databases, prompt engineering, and safety guardrails.

• Python development, REST APIs, and workflow automation; scripting in PowerShell or similar.

• Security architecture across identity, cloud, SaaS, endpoint, network, application, and data protection.

• SIEM management, log onboarding, detection engineering, and alert tuning.

• SOAR platforms, ticketing integrations, and automated playbook development.

Preferred

• Cloud and SaaS security: identity providers, CASB/SSE, DLP, key/secrets management.

• Application and API security, vulnerability scanning, DevSecOps, and secure SDLC.

• AI security and governance: NIST AI RMF, OWASP LLM Top 10, model risk, auditability, and policy enforcement.

• SIEM/SOAR platforms, endpoint security, web application firewalls, and threat intelligence tooling.

• ISO 27001, NIST CSF, privacy frameworks, and common risk management terminology.

Education & Experience

• Bachelor’s degree in Computer Science, Engineering, Cybersecurity, Data Science, or equivalent experience.

• 5+ years in cybersecurity, security engineering, application security, or a