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EY
EY
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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.

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Senior AI Engineer – EY, Chennai (Onsite)

Build enterprise AI solutions for EY Consulting clients, spanning Generative AI, retrieval-augmented generation, conversational AI, and AI agents. Contribute across solution design, implementation, testing, deployment, monitoring, and continuous improvement.

INIndiaOn-siteFull-timeSeniorEnglish RequiredAI EngineerMachine Learning Engineer
AzureCloud

Description

  • Design, develop, and implement AI, Generative AI, RAG, conversational AI, and agent-based solutions that address business needs
  • Translate solution blueprints into scalable components and reusable delivery patterns with architects, managers, and engineering teams
  • Build and maintain retrieval-augmented generation pipelines, prompt workflows, knowledge retrieval, integrations, APIs, and automation
  • Partner with data scientists, data engineers, application developers, and business stakeholders to deliver features and resolve technical challenges
  • Support the complete AI delivery lifecycle, from requirements and design through development, testing, deployment, monitoring, and improvement
  • Apply evaluation, validation, guardrails, quality controls, and performance optimization to AI solutions
  • Adhere to Responsible AI, privacy, security, compliance, and risk-management standards
  • Use Azure AI Foundry, Azure OpenAI, Databricks, vector databases, and related AI frameworks in solution delivery
  • Produce technical documentation, implementation notes, test evidence, solution walkthroughs, and stakeholder updates
  • Keep current with Generative AI, AI agents, multimodal systems, RAG techniques, prompt engineering, and enterprise AI platforms
  • Create reusable components, accelerators, templates, and supporting solution documentation
  • Support project leads with technical reporting, demonstrations, walkthroughs, estimates, and delivery updates
  • Mentor junior colleagues and contribute to building organizational AI capabilities

Requirements

  • Bring 4–8 years of professional experience, including hands-on work in AI/ML, Generative AI, data engineering, cloud AI platforms, or enterprise application development
  • Have practical experience delivering AI, Generative AI, Copilot, conversational AI, agentic AI, or RAG solutions in enterprise or client-facing settings
  • Demonstrate hands-on knowledge of AI/ML, Generative AI, RAG architectures, conversational AI, AI agents, and enterprise solution delivery
  • Hold a bachelor’s or master’s degree in Computer Science, Data Science, Engineering, Information Technology, or a related discipline
  • Understand large language models, Generative AI, RAG architectures, prompt engineering, conversational AI, and AI agents
  • Have experience with Azure AI Foundry, Azure OpenAI, Databricks, vector databases, enterprise search, orchestration frameworks, and APIs
  • Be able to build or support retrieval pipelines, embeddings, prompt workflows, data ingestion, model integration, and application integration
  • Understand AI evaluation, guardrails, hallucination detection, quality metrics, observability, security, privacy, and Responsible AI
  • Know software engineering practices, cloud deployment, APIs, databases, version control, CI/CD, MLOps, or LLMOps concepts
  • Be capable of diagnosing technical issues, improving performance, documenting implementations, and supporting pre-production or production AI systems
  • Bring strong analytical, problem-solving, collaboration, and communication abilities
  • Have hands-on enterprise, pre-production, or production AI experience; certifications, personal projects, and demos alone do not meet this requirement
  • Be able to explain one or two AI or Generative AI implementations, including the business need, personal contribution, technical approach, and outcomes

Benefits

  • Ongoing opportunities for learning and skills growth
  • Tools and flexibility to create meaningful impact
  • Access to insight, coaching, and leadership development
  • A diverse and inclusive working culture
  • The chance to support global clients and recognized brands
  • Collaboration with AI experts, analytics leaders, and industry specialists
  • Exposure to assignments across multiple client sectors
  • A global delivery network with opportunities for career development

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