Senior AI Security Engineer, Cyber Architecture, OT and Engineering
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Job Description
Sr. Agentic AI Engineer designing, building, and operationalizing agentic AI systems at EY. Working on multi-agent frameworks and intelligent automation to enhance cybersecurity posture.
Responsibilities:
- Architect, design, and deploy agentic AI workflows using frameworks such as LangChain, LangGraph, AutoGen, and related orchestration libraries.
- Build multi-agent systems capable of autonomous reasoning, planning, task delegation, and collaboration across cybersecurity functions.
- Implement agent-to-agent coordination strategies, including shared memory, messaging, goal decomposition, and tool-use patterns.
- Design and optimize Agent Development Kit (ADK)–based pipelines for secure, scalable agent deployment.
- Develop Retrieval-Augmented Generation (RAG) pipelines enabling agents to interact with real-time knowledge sources, logs, cybersecurity datasets, and enterprise APIs.
- Optimize vector embeddings, indexing strategies, and memory structures for high-accuracy decision support.
- Ensure grounded, auditable, and explainable outputs from LLM-based agents.
- Fine-tune, prompt-engineer, and configure LLMs/SLMs for specialized cybersecurity and automation tasks.
- Build reasoning, planning, and self-critique modules for agents to operate autonomously and safely.
- Integrate external LLM APIs, embeddings, synthetic data, and custom model endpoints.
- Lead the development of an enterprise-grade platform enabling orchestration of LLMs, RAG components, vector databases, and multi-agent protocols.
- Standardize the use of Model Context Protocol (MCP) for consistent context-sharing, memory management, and interoperability across agents.
- Build reusable agent templates, toolkits, and internal libraries to accelerate development across Cyber teams.
- Implement CI/CD, pipeline orchestration, versioning, and agent lifecycle management.
- Establish monitoring, tracing, and observability practices for autonomous system behavior.
- Automate manual cybersecurity processes through AI-driven workflow orchestration and dynamic agents.
- Extract, transform, and aggregate data from disparate cybersecurity sources such as SIEM, IAM, SOAR, endpoint telemetry, and API-driven security tools.
- Apply ML and statistical modeling techniques for anomaly detection, classification, optimization, and pattern recognition.
- Translate complex findings into intuitive visualizations and actionable insights for leadership.
- Work with cybersecurity SMEs, analysts, and engineers to identify opportunities for autonomous decision systems.
- Communicate complex AI concepts clearly to technical and non-technical audiences.
- Drive innovation and advocate for emerging AI technologies across the organization.
Requirements:
- 5+ years total experience in software development, AI/ML engineering, or data science
- 1+ year of Cybersecurity domain exposure, especially IAM (SailPoint, CyberArk) and SIEM/SOAR (Splunk, QRadar, etc.)
- 1+ year of hands-on experience building agentic AI or multi-agent applications, including LLM-driven workflows or reasoning systems
- Strong Python skills and working knowledge of SQL
- Direct experience with LLM/SLM APIs, embeddings, vector databases, RAG architecture, and memory systems
- Experience deploying AI workloads on GCP (Vertex AI) and IBM WatsonX
- Familiarity with agentic AI protocols, ADKs, LangGraph, AutoGen, or similar orchestration tools
- Practical experience implementing Model Context Protocol (MCP) for agent-level context management
- 1+ year experience with LangChain, LlamaIndex, OpenAI, Cohere, Anthropic, or similar frameworks
- Preferred 2+ years developing automation or RPA solutions
- 2+ years building on AWS, including serverless architectures
- Demonstrated experience with data visualization platforms (Tableau, Power BI, Looker)
- 2+ years working with APIs, microservices, and modern data engineering tooling
- Applied experience with agile software development practices
- Prior work deploying enterprise-scale agentic AI or autonomous reasoning systems
- Contributions to open-source AI/ML or agentic frameworks.
Benefits:
- Competitive salary
- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
- Remote work options
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