EY
EY

EY is a global professional services firm offering audit, tax, consulting, and advisory expertise. Its teams help organizations address complex business challenges, strengthen trust in financial reporting and markets, and use data and technology to support transformation.

The firm provides services including corporate finance advisory, transaction strategy, and technology consulting. EY works with clients across areas such as healthcare, legal services, marketing, energy, finance, and government, with sustainability and innovation informing many of its solutions.

Senior AI Engineer - EY Onsite in Chennai

Join EY as a Senior AI Engineer building enterprise GenAI, RAG, conversational AI, and agent solutions for consulting engagements. The role focuses on secure, scalable delivery across global client projects.

Description

  • Create and deliver AI, GenAI, RAG, conversational AI, and agent solutions that address business needs.
  • Translate solution designs into scalable technical components and repeatable implementation patterns.
  • Build and maintain RAG pipelines, prompt workflows, retrieval systems, integrations, APIs, and automation components.
  • Partner with data scientists, data engineers, application developers, architects, managers, and business stakeholders.
  • Contribute across requirements analysis, design, development, testing, deployment, monitoring, and ongoing improvement.
  • Apply AI evaluation, validation, guardrails, quality controls, and performance optimization techniques.
  • Adhere to Responsible AI, privacy, security, compliance, and risk management standards.
  • Use Azure AI Foundry, Azure OpenAI, Databricks, vector databases, and related AI frameworks.
  • Produce technical documentation, implementation notes, test findings, solution walkthroughs, and stakeholder updates.
  • Track developments in GenAI, AI agents, multimodal AI, RAG, prompt engineering, and enterprise AI platforms.
  • Create reusable components, accelerators, implementation templates, and solution documentation.
  • Assist with testing, validation, monitoring, issue resolution, and continuous improvement activities.
  • Provide project leads with technical updates, demonstrations, walkthroughs, estimates, and delivery status information.
  • Mentor junior colleagues and contribute to AI capability development.

Requirements

  • Bring 4–8 years of professional experience, including practical work with AI/ML, Generative AI, RAG architectures, conversational AI, AI agents, and enterprise AI delivery.
  • Have contributed hands-on to AI solutions in enterprise, pre-production, or production settings.
  • Be able to describe one or two AI or GenAI implementations, covering the business need, personal contribution, technical approach, and results.
  • Demonstrate practical experience with AI, GenAI, Copilot, conversational AI, agentic AI, or RAG solutions in enterprise or client-facing contexts.
  • Understand LLM application development, RAG pipelines, prompt engineering, vector databases, AI evaluation, APIs, cloud deployment, MLOps, or LLMOps through hands-on work.
  • Experience working with architects, managers, developers, data engineers, and business stakeholders is required.
  • Exposure to Azure AI Foundry, Azure OpenAI, Databricks, Microsoft Copilot, vector databases, or related AI ecosystems is preferred.
  • Hold a bachelor’s or master’s degree in Computer Science, Data Science, Engineering, Information Technology, or a related discipline.
  • Possess a strong foundation in Large Language Models, Generative AI, RAG architectures, prompt engineering, conversational AI, and AI agents.
  • Have developed or supported GenAI applications, copilots, chatbots, knowledge search tools, AI agents, or automation workflows.
  • Understand enterprise search, orchestration frameworks, APIs, embeddings, data ingestion, model integration, and application integration.
  • Know how AI evaluation, guardrails, hallucination checks, quality metrics, observability, security, privacy, and Responsible AI practices are applied.
  • Have working knowledge of software engineering, cloud deployment, APIs, databases, version control, CI/CD, MLOps, or LLMOps concepts.
  • Be capable of troubleshooting technical problems, improving performance, documenting implementations, and supporting production or pre-production AI solutions.
  • Demonstrate strong analytical, problem-solving, collaboration, and communication abilities.

Benefits

  • Competitive compensation.
  • Ongoing opportunities for learning and professional development.
  • Access to tools and flexibility to create meaningful impact.
  • Leadership development through insights, coaching, and confidence building.
  • A diverse and inclusive workplace culture.
  • The chance to support global clients and recognized brands.
  • Collaboration with AI experts, analytics leaders, and industry specialists.
  • Exposure to engagements across multiple client sectors.
  • Career pathways across the EY Global Delivery Services network.

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