Agentic AI engineer

As a Sr. Agentic AI Engineer at EY Cybersecurity, your role will involve 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. Your responsibilities will include: - 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. You will also be responsible for developing Retrieval-Augmented Generation (RAG) pipelines enabling agents to interact with real-time knowledge sources, logs, cybersecurity datasets, and enterprise APIs. Additionally, you will fine-tune, prompt-engineer, and configure LLMs/SLMs for specialized cybersecurity and automation tasks. Qualifications Required Skills: - 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.). - 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. Preferred Qualifications: - 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. At EY, the focus is on building a better working world by creating new value for clients, people, society, and the planet. EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow, working across a full spectrum of services in assurance, consulting, tax, strategy, and transactions. As a Sr. Agentic AI Engineer at EY Cybersecurity, your role will involve 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. Your responsibilities will include: - 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. You will also be responsible for developing Retrieval-Augmented Generation (RAG) pipelines enabling agents to interact with real-time knowledge sources, logs, cybersecurity datasets, and enterprise APIs. Additionally, you will fine-tune, prompt-engineer, and configure LLMs/SLMs for specialized cybersecurity and automation tasks. Qualifications Required Skills: - 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.). - 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. Preferred Qualifications: - 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. At EY,