People Consulting-AI in H2R-Senior

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. 

Role: AI in HR - Senior

The opportunity

As an AI in HR Senior Consultant, part of our People Consulting team, you will be responsible for developing and implementing AI-powered solutions and GenAI applications. You will work hands-on with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) frameworks, and cloud-native AI tools to deliver intelligent, scalable, and secure enterprise solutions.

You’ll collaborate closely with AI Architects, Functional consulting teams, and Product Owners to build and deploy next-generation AI in HR solutions that transform business processes and enhance user experiences.

Your Technical Responsibilities

• Develop client-ready Solutions, Proof of Concepts, Tools and Accelerators for AI in HR
• Maintain MS Copilot assets portfolio related to AI in HR
• Develop and implement Agentic AI and GenAI-based microservices and APIs for AI in HR
• Develop and integrate LLM-based solutions (OpenAI, Anthropic, Mistral, Azure OpenAI, etc.) for real-world enterprise use cases.
• Build and maintain RAG (Retrieval-Augmented Generation) pipelines involving embedding generation, document chunking, and vector search using relevant tools such as FAISS, Pinecone, or Weaviate.
• Implement prompt engineering, fine-tuning, and model evaluation techniques for optimizing responses and accuracy.
• Deploy AI models and services using cloud AI platforms (AWS Bedrock, Azure AI, Vertex AI)
• Work with data pipelines to preprocess, clean, and structure data for model ingestion.
• Develop API interfaces for integrating AI services into existing HR platforms and applications.
• Ensure strong adherence to DevOps/MLOps practices, including versioning, CI/CD automation, monitoring, and rollback strategies.
• Collaborate with the architecture and DevOps teams for containerized deployments using Docker and Kubernetes.
• Implement logging, monitoring, and performance tracking for deployed AI models and APIs.
• Continuously explore emerging AI frameworks, open-source models, and new deployment patterns to enhance solution design.

Your Management & Collaboration Responsibilities:

• Collaborate with HR Functional Consultants, AI Architects and cross-functional teams to convert solution blueprints into implementable modules.
• Participate in technical discussions, design reviews, and sprint planning to ensure smooth delivery.
• Support project managers in defining realistic timelines and technical dependencies.
• Maintain high-quality documentation for models, APIs, and data pipelines.
• Contribute to proofs of concept (POCs) and internal accelerators showcasing new AI capabilities.
• Assist in evaluating third-party tools, APIs, and frameworks for AI adoption within enterprise systems.

Your People Responsibilities (If Applicable):

• Support peer learning through internal demos and technical discussions.
• Share best practices in AI standards, prompt design, and data preparation.

Requirements (Qualifications):

Education:

• BE/BTech with 4–8 years of total experience, including 1–2 years of relevant AI/ML or GenAI project experience.

Mandatory Skills:

• Understanding of end-to-end HR process lifecycle
• Experience with prompt optimization and evaluation
• Programming: Python (preferred), Java, or Node.js
• AI/ML Frameworks: LangChain, LlamaIndex, Hugging Face Transformers, OpenAI API, Azure OpenAI, or Anthropic API
• LLM Expertise: Experience with GPT, Claude, Llama, Mistral, or other open-source LLMs
• RAG Frameworks: Pinecone, FAISS, Chroma, or Weaviate
• Cloud AI Platforms: AWS Bedrock, Azure Cognitive Services, Google Vertex AI
• APIs & Integration: REST/gRPC APIs, Swagger/OpenAPI, Postman
• Data & Storage: MySQL, MongoDB, Redis, or vector stores
• DevOps/MLOps: Git, Docker, Kubernetes, CI/CD (GitHub Actions, Jenkins), MLflow (nice to have)
• Testing: PyTest, Postman, and API-level testing
• Version Control: Git/GitHub, Bitbucket
• Data visualization: Power BI, Tableau

Preferred Skills:

• Experience in implementation of HRMS platforms (Workday, SAP SuccessFactors, etc.)
• Familiarity with LangGraph or CrewAI for agentic workflows
• Basic knowledge of transformer architecture internals
• Experience working with data pipelines (Airflow, Prefect)
• Awareness of responsible AI and model governance principles
• Agile/DevOps delivery experience

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