AI Security Automation Engineer, AVP
Build and deploy AI-driven cybersecurity automation systems, including agents and RAG pipelines, on cloud platforms to detect and respond to threats for a global financial firm.
- Compensation
- Not disclosed
- Location
- Singapore, Singapore
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Industrial engineering
- Posted
Skills
Full description
Who we are looking for
State Street's Cyber Data & Analytics (CyberDNA) team is seeking a Junior AI Security Automation Engineer to join our team to help shape the next generation of cybersecurity data, analytics, and AI-powered platforms. Partnering closely with Global Cyber Security teams, Infrastructure Teams, and Enterprise Continuity Services, this team develops advanced data platforms, intelligent automation solutions, and engineering capabilities that enable cybersecurity teams to make faster, AI-driven decisions and strengthen the firm's ability to detect, prevent, and respond to evolving cyber threats.
Why this role is important to us
Through innovation in AI, analytics, and automation, CyberDNA team plays a critical role in protecting State Street, its clients, and its partners from increasingly sophisticated global threat actors. This role sits at the intersection of Artificial Intelligence, Cybersecurity, Data Engineering, and Full-Stack Software Development, with a primary focus on enabling secure, scalable, and governed AI adoption across the enterprise for supporting Cyber Security functions. The successful candidate will be part of a global AI security automation engineering team focused on delivering next-generation AI platforms, autonomous agents, security automation solutions, and data-driven applications that strengthen cyber resilience, accelerate innovation, and transform cybersecurity operations through intelligent automation.
What you will be responsible for
As Junior AI Security Automation Engineer, you will, under the guidance from a Lead/Senior Engineer:
- Build production-grade AI systems including agents, skills, memory patterns, guardrails, and tool-use orchestration
- Build 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
- 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
- Follow defined engineering standards for reliability, security, and safe AI operation across the platform lifecycle
- 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.