EY is seeking a skilled AI Engineer to spearhead the development, deployment, and operation of enterprise-grade AI and Agentic AI solutions. This hands-on role focuses on building LLM-powered applications, orchestration, and multi-agent workflows. You will leverage Azure AI Foundry and Azure-native services, ensuring solutions are secure, scalable, observable, and governed throughout their lifecycle.

Partnering closely with engineering leads, architects, and data science teams, you'll translate AI use cases into robust, enterprise-ready systems. A key aspect of this role involves embedding evaluation, quality monitoring, and runtime security into AI systems, utilizing advanced patterns like LLM-as-a-Judge and adhering to agent lifecycle governance.

This is an opportunity to shape how AI is built, deployed, and managed across the organization, moving beyond isolated proofs of concept to deliver tangible, reliable, and scalable AI solutions. Join us to build an exceptional career and contribute to a better working world.

Design and build cutting-edge Agentic AI solutions using Azure AI Foundry and Azure-native services. Develop sophisticated orchestration layers and multi-agent systems for complex task execution. Engage in full-stack engineering, creating end-to-end AI experiences, backend services, and secure API integrations. Implement serverless and asynchronous processing using Azure Functions, including Durable Functions for stateful orchestration. Utilize messaging and queue-based patterns to enhance the reliability of AI pipelines and workflows. Work with ADLS-style data lake patterns for efficient data ingestion, storage, and processing to support AI workloads. Integrate Azure Cognitive Services and Azure AI Services to enhance end-to-end AI solution capabilities. Implement vector databases and knowledge stores, such as Azure AI Search, for effective retrieval. Develop continuous evaluation pipelines for LLM and agent outputs using LLM-as-a-Judge patterns. Ensure AI solutions align with enterprise governance, including agent lifecycle management, access controls, and observability. Implement and support runtime security measures for agentic solutions, focusing on threat detection and monitoring.

Proven expertise in core software engineering with strong development skills in Python, C#, TypeScript, or JavaScript. Demonstrated experience in building API-driven services and integrating distributed systems, with a solid understanding of non-functional requirements like reliability, scalability, and performance. Hands-on experience with Azure AI Foundry for enterprise GenAI solution delivery and extensive use of Azure Functions, including Durable Functions, for serverless and asynchronous workloads. Proficiency in employing message queues and event-driven patterns for decoupled and reliable workflows, alongside experience with ADLS for data management in AI contexts. Practical experience with vector databases and vector search, including enterprise deployment patterns, and implementing LLM-as-a-Judge for AI output evaluation. Familiarity with Agent 365 (A365) concepts for agent lifecycle management, governance, and observability, as well as experience in delivering solutions with robust runtime security and protection expectations. Possession of a Python Certification and certifications in Azure AI Services and Azure Data Services are highly desirable.