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Ernst & Young

Global professional services: consulting, assurance, tax

AMS-DE-Aiops-Engineer-Manager

Engineering LeadershipUpdated on Nov 14
Full-timeThiruvananthapuram, Kerala, IndiaNo salary listedIn-person

About the Job

Requirements

  • Bachelor’s or master’s degree in computer science, engineering, or a related field.
  • At least 5 years of professional software engineering experience, including at least 2–3 years designing, developing, and deploying Generative AI, Agentic AI, intelligent automation, or AI-powered solutions in enterprise environments.
  • Proven experience building and implementing solutions using Large Language Models, Retrieval-Augmented Generation, prompt engineering, agent orchestration frameworks, and AI-powered workflows.
  • Hands-on experience with AI/ML frameworks, natural language processing technologies, vector databases, semantic search, and enterprise knowledge retrieval systems.
  • Strong programming expertise in Python and working knowledge of JavaScript/TypeScript, including experience developing APIs, automation services, and enterprise integrations.
  • Understanding of AIOps, MLOps, LLMOps, model evaluation, monitoring, observability, and governance practices for production AI systems.
  • Experience with multi-agent systems, Model Context Protocol, AI copilots, and enterprise AI platforms.
  • Hands-on experience with Large Language Models, prompt engineering, Retrieval-Augmented Generation, AI agents, and agent orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, or similar technologies.
  • Strong understanding of Generative AI, natural language processing, machine learning concepts, and integration of AI services into enterprise workflows.
  • Experience integrating AI, automation, and enterprise systems through REST APIs, software development kits, 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, Amazon Web Services, or Google Cloud, including AI and machine learning services.
  • Familiarity with AI governance, Responsible AI principles, security, privacy, and regulatory compliance requirements.
  • Ability to collaborate across AI, engineering, operations, platform, and business teams, and mentor team members while driving technical leadership and engineering best practices across engagements.

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, 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 Large Language Models, natural language processing, computer vision, and other AI/ML services into enterprise applications and platforms through APIs, software development kits, 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 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 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 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.

Desired Qualifications

  • Knowledge of vector databases, embeddings, knowledge graphs, semantic search, and enterprise data integration patterns.
  • Experience building AI, Generative AI, and automation solutions, accelerators, and reusable frameworks within managed services or large-scale enterprise environments.
  • Understanding of IT service management, Information Technology Infrastructure Library, DevOps, MLOps, LLMOps, and operational governance practices.

About the Company

Ernst & Young

Global professional services: consulting, assurance, tax

EY (Ernst & Young) provides professional services at a global scale, offering consulting, assurance, tax, and transaction advisory services. It serves clients across industries such as technology, media, real estate, hospitality, and construction. Instead of selling a single product, EY works with clients through tailored engagements where cross-disciplinary teams analyze challenges, design strategies, perform audits, help with tax planning, and assist with mergers or divestitures. What sets EY apart is its worldwide reach and integrated service model, industry-specific expertise, and focus on responsible business practices like sustainability, cybersecurity, and workforce flexibility. EY’s goal is to help organizations improve performance, manage risk, and achieve sustainable growth while building a better working world.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Boston, MA
Founded
1991

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