Senior AI Security Automation Engineer

About the role

The Senior AI Security Automation Engineer will play a crucial role in shaping the next generation of cybersecurity data, analytics, and AI-powered platforms. This role involves partnering closely with Global Cyber Security teams, Infrastructure Teams, and Enterprise Continuity Services to develop advanced data platforms, intelligent automation solutions, and engineering capabilities that enable faster, AI-driven decision-making and enhance the firm's cyber resilience.

Responsibilities

• Drive the architecture and hands-on delivery of scalable, reliable agentic AI platforms for security workflows
• Design and build production-grade AI systems including agents, skills, memory patterns, guardrails, and tool-use orchestration
• Architect retrieval and context-engineering approaches including embeddings, semantic search, grounding, summarization, and prompt/version management
• Engineer cloud-native AI services in AWS, Azure and GCP using containers and serverless patterns, event-driven messaging, and distributed data stores
• Optimize platform performance across latency, throughput, scalability, caching, context efficiency, and cost controls
• Build well-governed APIs and integrations that connect AI capabilities to security platforms, tools, and business processes
• Establish evaluation, research, regression testing, and observability frameworks to continuously improve quality and agent behavior
• Define engineering standards for reliability, security, and safe AI operation across the platform lifecycle
• Mentor junior engineers and influence engineering direction through code reviews, architecture forums, and cross-team technical leadership
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation

Qualifications

• Demonstrated experience architecting, developing, and deploying production-grade Generative AI and Large Language Model (LLM) based solutions, including agentic workflows, intelligent agents, and enterprise tool integration frameworks
• Strong software engineering fundamentals with expertise in designing and delivering cloud-native applications and services leveraging containers, serverless architectures, and modern public cloud platforms
• Proven experience building highly scalable distributed systems utilizing asynchronous processing, event-driven architectures, durable messaging, and high-performance data access patterns
• Hands-on expertise developing Retrieval-Augmented Generation (RAG) solutions, including embeddings, semantic search, knowledge grounding, context engineering, prompt optimization, and prompt lifecycle management
• Experience implementing AI evaluation, testing, monitoring, and observability frameworks to measure model quality, reliability, performance, and safe operation in production environments
• Strong API design and integration experience, including the development of secure, reusable, and scalable platform services that enable enterprise-wide adoption of AI capabilities
• Strong technical leadership skills with a track record of mentoring engineers, driving architectural decisions, influencing technology strategy, and collaborating effectively with cross-functional stakeholders
• Hands-on experience utilizing enterprise-approved AI-assisted software development tools to accelerate application delivery, improve code quality, streamline testing, and enhance documentation, while ensuring outputs are validated through secure coding practices, peer review, and automated testing
• Deep understanding of cybersecurity data sources, including endpoint, network, application, cloud, and system telemetry, and their application in security monitoring, analytics, and automation
• Experience working with Security Information and Event Management (SIEM) platforms and cybersecurity analytics solutions to ingest, correlate, retrieve, and analyze large-scale security data
• Strong understanding of cybersecurity operations, including threat detection, incident response, threat hunting, security analytics, and security automation
• Proven ability to lead and influence geographically distributed teams through virtual collaboration, fostering strong partnerships, driving technical outcomes, and building effective relationships across engineering, security, and business organizations
• Strong understanding of CI/CD tools (Jenkins, Harness, Spinnaker, Argo CD, etc.) and methodology, production experience in designing and implementing CI/CD pipelines with a focus on helping teams release frequently to production while maintaining deployment reliability
• Experience developing cybersecurity, analytics, or operational intelligence solutions
• Experience developing complex technical initiatives while remaining deeply hands-on

Skills

• Python, JavaScript/TypeScript, Rust, Go (Golang), Bash, and PowerShell
• Knowledge of Responsible AI, data governance, and model risk management

Benefits

• Retirement savings plan (401K) with company match
• Insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages
• Paid-time off including vacation, sick leave, short term disability, and family care responsibilities
• Access to Employee Assistance Program
• Incentive compensation including eligibility for annual performance-based awards (excluding certain sales roles subject to sales incentive plans)
• Eligibility for certain tax advantaged savings plans

Pay

$120,000 - $202,500 Annual

Schedule

Work shift is 8 AM – 5 PM local time with occasional Level 2-3 escalation resolution to support operational incidents. Hybrid role includes an in-office presence requirement of 2–4 days per week, consistent with the organization's hybrid work policy.