Senior AI Security Automation Architect

State Street

Princeton (NJ)

Hybrid

USD 120,000 - 202,500

Full time

14 days+

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Job summary

State Street is seeking a Senior AI Security Automation Engineer to shape AI-powered security platforms, partnering with CyberDNA and global teams. You will design agentic AI systems, orchestrate tools, and ensure secure, scalable AI adoption across security operations.

Responsibilities include building cloud-native AI services, improving observability, and mentoring engineers while aligning with secure coding practices and governance. Hybrid in-office role with global impact.

Qualifications

Master’s or bachelor’s degree in computer science, software engineering, AI, data science, cybersecurity, or related discipline.
7+ years of professional software engineering experience.
3+ years of experience developing AI, machine learning, or generative AI solutions.
Demonstrated success designing and deploying enterprise-scale applications and platforms.
Experience developing cybersecurity, analytics, or operational intelligence solutions.

Responsibilities

Drive the architecture and hands-on delivery of scalable 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 and productivity; ensures outputs validated through peer review and secure coding standards.