Join EY's Global Delivery Services (GDS) TechOps practice as a Manager, driving innovation in AI engineering and automation. You will lead a team in designing and operationalizing intelligent AI agents and autonomous workflows using LLMs and enterprise integrations. This role offers the chance to build a career in a globally connected, inclusive culture, contributing to a better working world.

EY's GDS is a worldwide network of service delivery centers crucial to EY's growth strategy, with over 80,000 professionals across ten global locations. Our teams provide exceptional client service in Consulting, Assurance, Tax, Strategy & Transactions, and Knowledge support, alongside cost-effective Enablement Services. Our innovation specialists drive advancements in analytics, digital, mobile technology, and more.

Lead and mentor a team of AI Engineers, Developers, and Solution Architects, fostering a high-performance, innovative culture. Own the end-to-end delivery of AI and automation projects, ensuring quality, timeliness, and budget adherence. Design, develop, and deploy Agentic AI solutions using LLMs, multi-agent architectures, and orchestration frameworks to automate complex workflows.

Architect and implement AI-powered autonomous workflows and intelligent agents for reasoning, planning, and task execution across enterprise systems. Integrate AI/ML services, including NLP and Computer Vision, into enterprise applications. Transform repetitive processes into scalable AI and automation solutions using Python and modern AI frameworks. Collaborate with cross-functional teams to define agent behaviors, integrate tools, and establish success metrics.

Monitor, maintain, and optimize AI agents for reliability and performance. Establish technical standards, reusable components, and best practices for Agentic AI. Create technical documentation and solution designs. Evaluate emerging AI technologies and drive adoption of AI solutions. Provide technical leadership, mentorship, and support business development activities. Ensure compliance with security, governance, and responsible AI standards.

A Bachelor's or Master's degree in Computer Science, Engineering, or a related field is required, alongside 5+ years of professional software engineering experience, with 2-3 years focused on Generative AI, Agentic AI, or intelligent automation in enterprise settings.

Proficiency in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and agent orchestration frameworks like LangChain or AutoGen is essential. Experience with Generative AI, NLP, machine learning concepts, and integrating AI services via REST APIs, SDKs, and cloud-native architectures is crucial. Strong Python programming expertise and working knowledge of JavaScript/TypeScript are necessary.

Familiarity with AIOps, MLOps, LLMOps, model evaluation, monitoring, observability, and governance practices for production AI systems is important. Experience with multi-agent systems, AI copilots, and enterprise AI platforms, along with cloud platforms such as Azure, AWS, or GCP, is highly desirable. An understanding of ITSM, ITIL, DevOps, and responsible AI principles is beneficial.