EY - GDS Consulting - AIA - Nvidia AI Engineer- Senior

AIA – NVIDIA AI ENGINEER (PHYSICAL & AGENTIC AI)

The opportunity

We are the only professional services organization who has a separate business dedicated exclusively to the financial services marketplace. Join Digital Engineering Team and you will work with multi-disciplinary teams from around the world to deliver a global perspective. Aligned to key industry groups including Asset management, Banking and Capital Markets, Insurance and Private Equity, Health, Government, Power and Utilities, we provide integrated advisory, assurance, tax, and transaction services. Through diverse experiences, world-class learning and individually tailored coaching you will experience ongoing professional development. That’s how we develop outstanding leaders who team to deliver on our promises to all of our stakeholders, and in so doing, play a critical role in building a better working world for our people, for our clients and for our communities. Sound interesting? Well, this is just the beginning. Because whenever you join, however long you stay, the exceptional EY experience lasts a lifetime.

We are looking for a Senior– NVIDIA AI Engineers build physical and agentic AI systems using the NVIDIA AI Enterprise ecosystem, with 4+ years of strong hands-on experience in designing and delivering enterprise-grade AI solutions. The role requires deep technical proficiency in Python, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI frameworks, and cloud platforms (Azure, AWS, GCP), combined with the ability to lead teams, drive innovation, and translate complex AI capabilities into measurable business outcomes. In this role, you will contribute in two key capacities:

• by leading the design, development, and deployment of GenAI and Agentic AI solutions — including LLM-based applications, multi-agent systems, and RAG pipelines — aligned to target-state architecture and client objectives, and
• by driving AI strategy, proof-of-concept initiatives, and production-grade implementations across industry verticals, leveraging cloud-native services, MLOps practices, and emerging AI technologies to deliver scalable, observable, and high-impact automation solutions..

EY’s Artificial Intelligence & Automation (AIA) team is a specialized, intelligence‑driven business unit that combines advanced AI, automation engineering, and deep domain knowledge to deliver transformative enterprise solutions. The AIA practice partners with clients to analyze, design, and operationalize AI‑led automation strategies that accelerate digital transformation and unlock measurable business value. We address organizations’ most critical challenges across process optimization, intelligent workflows, data‑driven decisioning, Generative AI adoption, and automation-enabled innovation. With a unique ability to translate AI strategy into actionable architectures, scalable platforms, and production‑grade automations, EY’s AIA team helps clients build sustainable competitive advantage, enhance productivity, and navigate disruption by embedding intelligence at the core of their business and technology ecosystems.

Your key responsibilities

AI Strategy & Solution Design

• Design AI-assisted and agentic workflows
• Develop AI systems using NVIDIA AI Enterprise
• Work with NVIDIA NIM™, Omniverse™, or Isaac Sim™
• Optimize AI workloads on GPUs
•  Knowledgeable in Physical AI

GenAI & Agentic AI Development

• Architect and build production-grade applications using Large Language Models (GPT, Claude, LLaMA, Gemini), including prompt engineering, fine-tuning, and evaluation.
• Design and implement Retrieval-Augmented Generation (RAG) pipelines using Vector Databases, Knowledge Graphs, and hybrid retrieval strategies.
• Build multi-agent orchestration systems using frameworks such as LangGraph, AutoGen, CrewAI, or LlamaIndex, with memory management and tool integrations.
• Develop robust API layers, integration services, and data pipelines to connect AI capabilities with enterprise systems.
• Apply strong analytical thinking, structured problem-solving, and clear technical communication in solution design.

MLOps, Cloud & Observability

• Implement MLOps practices and tools — CI/CD for ML, containerization (Docker, Kubernetes), model versioning, and reproducibility — to ensure reliable AI deployments.
• Deploy and manage AI workloads on cloud platforms (Azure, AWS, GCP), leveraging services such as Azure OpenAI, Azure AI Search, SageMaker, or Vertex AI.
• Build observability into AI systems — monitoring latency, model drift, token usage, performance metrics, and guardrails for responsible AI.
• Ensure seamless integration of optimized solutions into the overall product or system architecture.

Team Leadership & Collaboration

• Mentor and guide team members on AI/ML best practices, emerging GenAI technologies, and engineering standards through design discussions, code reviews, and knowledge sharing.
• Keep the team updated on the latest advancements in GenAI, Agentic AI, and related technologies to bring innovative solutions to engagements.
• Support all phases of delivery including sprints, testing cycles, deployments, and hypercare, ensuring timely delivery under tight timelines.
• Present solutions, architecture decisions, and results to both technical and business stakeholders with strong written and verbal communication.

Required Skills

• 4+ years of relevant professional experience with a strong foundation in AI/ML, with 4–6 years of AI/ML engineering experience.
• Expertise in:
  • Core AI/ML: Python, PyTorch, TensorFlow, Hugging Face Transformers, ML algorithms, feature engineering, model evaluation
  • Strong Python and PyTorch skills
  • Experience with NVIDIA GPUs and CUDA

Good to Have

• Exposure to:
  • Experience working with LLMs or GenAI tools

Preferred Qualifications

• Certifications in Azure AI (preferred), AWS Machine Learning, or GCP Professional ML Engineer.
• Published research, patents, or conference talks in AI/ML or NLP domains.
• Certifications or hands-on experience in MLOps, Kubernetes, or DevOps for AI.

Education:

• Degree: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics, or a related field, or equivalent practical experience

What we offer

EY Global Delivery Services (GDS) is a dynamic and truly global delivery network. We work across six locations – Argentina, China, India, the Philippines, Poland and the UK – and with teams from all EY service lines, geographies and sectors, playing a vital role in the delivery of the EY growth strategy. From accountants to coders to advisory consultants, we offer a wide variety of fulfilling career opportunities that span all business disciplines. In GDS, you will collaborate with EY teams on exciting projects and work with well-known brands from across the globe. We’ll introduce you to an ever-expanding ecosystem of people, learning, skills and insights that will stay with you throughout your career.

• Continuous learning: You’ll develop the mindset and skills to navigate whatever comes next.
• Success as defined by you: We’ll provide the tools and flexibility, so you can make a meaningful impact, your way.
• Transformative leadership: We’ll give you the insights, coaching and confidence to be the leader the world needs.
• Diverse and inclusive culture: You’ll be embraced for who you are and empowered to use your voice to help others find theirs.