AMS-DE-AIOps-Engineer-Manager

The Opportunity

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, semantic search, and enterprise data integration patterns is highly desirable.
• Experience building AI, GenAI, automation solutions, accelerators, and reusable frameworks within managed services or large-scale enterprise environments is preferred.
• Understanding ITSM, ITIL, DevOps, MLOps, LLMOps, and operational governance practices is an added advantage.
• Familiarity with AI governance, Responsible AI principles, security, privacy, and regulatory compliance requirements.
• Excellent communication and stakeholder management skills, with the ability to collaborate effectively across AI, engineering, operations, platform, and business teams.
• Ability to mentor team members, contribute to technical leadership, and drive the adoption of Agentic AI, automation, and engineering best practices across engagements.

To qualify for the role, you must have

• Bachelor’s or master’s degree in computer science, Engineering, or related field.
• 5+ years of professional software engineering experience, with at least 2-3 years of hands-on experience designing, developing, and deploying Generative AI, Agentic AI, intelligent automation, or AI-powered solutions in enterprise environments.
• Proven experience building and implementing solutions utilizing Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, agent orchestration frameworks, and AI-powered workflows.
• Hands-on experience with AI/ML frameworks, NLP technologies, vector databases, semantic search, and enterprise knowledge retrieval systems.
• Strong programming expertise in Python and working knowledge of JavaScript/TypeScript, with experience developing APIs, automation services, and enterprise integrations.
• Understanding AIOps, MLOps, LLMOps, model evaluation, monitoring, observability, and governance practices for production AI systems.
• Experience with multi-agent systems, MCP (Model Context Protocol), AI copilots, and enterprise AI platforms.

What we look for:

• Passionate and curious technologists with a strong interest in Generative AI, Agentic AI, intelligent automation, and emerging AI technologies, coupled with hands-on experience in Python development and enterprise integrations.
• Continuous learners who stay current with advancements in LLMs, AI agents, RAG architecture, agent orchestration frameworks, and cloud-based AI services.
• Strong problem solvers with the ability to analyze complex business challenges, identify automation opportunities, and design innovative AI-driven solutions.
• Self-motivated professionals who take ownership of outcomes and proactively troubleshoot, optimize, and enhance AI-enabled workflows and systems.
• Collaborative team players who can effectively partner with AI, engineering, platform, operations, and business sta