Join EY's People Consulting team as a Senior Consultant specializing in AI-enabled HR Transformation. In this role, you will empower clients by identifying, designing, and implementing cutting-edge AI solutions across the entire HR and workforce lifecycle. Your expertise in HR, consulting, and AI will be instrumental in translating complex business challenges into practical, responsible, and scalable solutions.

You will collaborate closely with HR leaders, functional consultants, product owners, data specialists, and technical teams. Your work will involve defining key use cases, redesigning HR processes, developing detailed functional requirements, supporting solution implementation, and driving the adoption and realization of value from these AI initiatives.

Assess and identify high-value AI, GenAI, and agentic AI opportunities within HR processes. Facilitate discovery workshops with stakeholders to translate business needs into concrete use cases, user journeys, and functional requirements. Redesign HR processes and operating models to seamlessly integrate human-AI collaboration.

Develop client-ready solutions, Proofs of Concept, tools, and accelerators focused on AI in HR. Maintain and update MS Copilot assets related to AI in HR. Define functional logic, knowledge requirements, prompts, workflows, and guardrails for AI solutions. Coordinate with architects, developers, and data teams to bring functional designs to life.

Lead functional and user acceptance testing to ensure AI outputs meet quality and performance standards. Build and integrate LLM-based solutions using platforms like OpenAI, Anthropic, and Azure OpenAI for enterprise use cases. Develop and maintain RAG pipelines, implementing prompt engineering and model evaluation techniques for optimal accuracy.

Deploy AI models and services using cloud AI platforms such as AWS Bedrock, Azure AI, and Vertex AI. Work with data pipelines for preprocessing and structuring data for model ingestion. Develop API interfaces for seamless integration of AI services into existing HR platforms. Ensure strong adherence to MLOps practices, including versioning, CI/CD, monitoring, and rollback strategies.

Collaborate with architecture and DevOps teams for containerized deployments using Docker and Kubernetes. Implement robust logging, monitoring, and performance tracking for deployed AI models and APIs. Continuously explore emerging AI frameworks and deployment patterns to enhance solution design. Support responsible AI assessments, focusing on privacy, security, bias, transparency, and human oversight.

We are seeking candidates with a Bachelor's degree in Engineering or Technology (BE/BTech) and 4-8 years of overall professional experience, including 1-2 years specifically in AI/ML or GenAI projects. An MBA or M.Tech degree with a relevant specialization is considered an advantageous bonus.

Key technical skills include an in-depth understanding of the end-to-end HR process lifecycle. Proficiency in programming languages such as Python (preferred), Java, or Node.js is essential. Expertise in AI/ML is crucial, encompassing LLMs (GPT, Claude, Llama, Mistral), fine-tuning, prompt engineering, embeddings, and vector search.

Architectural experience should include RAG design, Model Context Protocol (MCP), multi-agent system design, and microservices integration across HR systems. Familiarity with cloud AI platforms like AWS Bedrock, Azure OpenAI, and GCP Vertex AI is required. Experience with SQL/NoSQL databases, vector databases (Pinecone, FAISS, Weaviate), and Redis is also necessary.

Understanding of security and compliance protocols like OAuth/SAML, data governance, and model safety frameworks is important. Data visualization skills using Power BI or Tableau are beneficial. Proficiency in version control and collaboration tools such as Git/GitHub, Jira, and Confluence is expected.

Familiarity with AI-driven software agents using frameworks like LangGraph or CrewAI, alongside experience in Agile/Scrum/SAFe methodologies, is highly valued. Preferred skills include experience implementing HRMS platforms (Workday, SAP SuccessFactors), multi-modal AI, knowledge of transformer architecture, MLOps and deployment tools (Docker, Kubernetes, MLflow), contributions to open-source AI projects, and experience applying responsible AI principles.