AMS-DE-AIOps-Engineer-Manager

Position Title: TechOps - Digital Engineering Operations - AI Engineer - Manager

As a Manager in EY GDS Tech Ops practice, you will be responsible for hands-on technical leadership, stakeholder collaboration, and delivery ownership, designing, and operationalizing intelligent AI agents and autonomous workflows that leverage LLMs, AI services, and enterprise integrations. The role requires strong expertise in AI engineering, automation, software development, and cross-functional collaboration to deliver scalable, secure, and business-impacting Agentic AI solutions.

Your Key Responsibilities

• Lead and manage a team of AI Engineers, Developers, and Solution Architects, providing technical guidance, coaching, mentoring, and career development support.
• Create a high-performance culture focused on innovation, accountability, collaboration, and continuous improvement.
• Own end-to-end delivery of AI and automation engagements, ensuring quality, timelines, budget adherence, and stakeholder satisfaction.
• Design, develop, and deploy Agentic AI solutions leveraging Large Language Models (LLMs), multi-agent architectures, retrieval systems, and AI orchestration frameworks to automate complex business and engineering workflows.
• Architect and implement AI-powered autonomous workflows and intelligent agents capable of reasoning, planning, decision-making, and executing tasks across enterprise systems.
• Integrate LLMs, NLP, Computer Vision, and other AI/ML services into enterprise applications and platforms through APIs, SDKs, and cloud-native architectures.
• Identify, analyze, and transform repetitive and high-value operational and engineering processes into scalable AI and automation solutions.
• Develop custom applications, services, and automation logic using Python and modern AI frameworks to connect disparate systems and enable end-to-end workflow automation.
• Collaborate with cross-functional teams to define agent behaviors, tool integrations, guardrails, evaluation frameworks, and success metrics for AI solutions.
• Monitor, maintain, troubleshoot, and continuously optimize AI agents and automated workflows to ensure reliability, scalability, security, and performance.
• Establish technical standards, reusable components, best practices, and reference architectures for Agentic AI and automation implementations.
• Create and maintain technical documentation, solution designs, operational runbooks, and deployment guidelines for AI-powered automation solutions.
• Collaborate closely with AI Platform, Engineering, Operations, and Business teams to identify, integrate, and operationalize AI services, tools, accelerators, and enterprise AI capabilities.
• Evaluate emerging AI technologies, frameworks, and agent orchestration platforms, recommending innovative solutions that drive business value and operational efficiency.
• Drive adoption of AI, Agentic AI, automation solutions, and reusable accelerators across engagements, practices, and client programs.
• Provide technical leadership and mentorship to engineers, contributing to solution design reviews, code quality, architecture governance, and engineering best practices.
• Support business development activities related to AI and automation, including solution design, proposals, client workshops, demonstrations, and technical presentations.
• Ensure all AI and automation solutions comply with organizational security, governance, risk management, privacy, and responsible AI standards.
• Contribute to resource planning and technical execution by estimating effort, prioritizing work, coordinating with stakeholders, and ensuring successful delivery of AI initiatives.

Skills and attributes for success

• Hands-on experience with Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, and agent orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, or similar technologies.
• Strong understanding of Generative AI, NLP, machine learning concepts, and integration of AI services into enterprise workflows.
• Experience integrating AI, automation, and enterprise systems through REST APIs, SDKs, event-driven architectures, and cloud-native services.
• Ability to analyze complex business and engineering processes and design scalable Agentic AI and intelligent automation solutions that deliver measurable business value.
• Experience developing and deploying autonomous workflows leveraging AI agents, tool calling, workflow orchestration, and decision-making frameworks.
• Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud, including AI and machine learning services.
• Knowledge of vector databases/embeddings/knowledge graphs is highly desirable.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.