Sr. Agentic AI Engineer

About the job

As a Sr. Agentic AI Engineer at EY Cybersecurity, your role involves designing, building, and operationalizing agentic AI systems, multi-agent frameworks, and intelligent automation solutions to enhance the cybersecurity posture. You will leverage advanced machine learning, LLM engineering, reasoning systems, and data engineering to solve enterprise-scale problems and drive the next generation of autonomous cyber-analytics capabilities. **Key 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. - Develop Retrieval-Augmented Generation (RAG) pipelines enabling agents to interact with real-time knowledge sources, logs, cybersecurity datasets, and enterprise APIs. - Fine-tune, prompt-engineer, and configure LLMs/SLMs for specialized cybersecurity and automation tasks. - Lead the development of an enterprise-grade platform enabling orchestration of LLMs, RAG components, vector databases, and multi-agent protocols. - Implement CI/CD, pipeline orchestration, versioning, and agent lifecycle management. - Extract, transform, and aggregate data from disparate cybersecurity sources and apply ML and statistical modeling techniques for anomaly detection, classification, optimization, and pattern recognition. - Work with cybersecurity SMEs, analysts, and engineers to identify opportunities for autonomous decision systems. **Qualifications:** - 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.

Requirements

• LLM engineering
• Machine Learning
• Python
• SQL
• Data Engineering

Preferred Technologies

• LLM engineering
• Machine Learning
• Python
• SQL
• Data Engineering

About the company

As a global leader in advisory, assurance, tax, and transactions, EY-Parthenon operates at the intersection of business and technology, helping clients create long-term value. They leverage advanced LLM engineering, reasoning systems, and data engineering to solve enterprise-scale problems and drive autonomous cyber-analytics capabilities.