DE-AI Senior Manager-BFA-GDSF04

Career Family  

EY-DET-FS

Role Type   

Sr AI Architect

The opportunity

As an AI Architect, part of our EY-DET-FS team, you will lead the design, development, and deployment of

AI-first enterprise architecture. You will work at the intersection of cloud-native systems, large language models (LLMs), multimodal AI, and Retrieval-Augmented Generation (RAG), Knowledge Augmented Graph (KAG) frameworks to deliver cutting-edge intelligent applications.

You will play a pivotal role in guiding teams, defining AI architecture blueprints, and making strategic technology decisions that enable scalable, secure, and responsible AI adoption across global client engagements.

Your Technical Responsibilities

• Architect and design AI and GenAI-based solutions, integrating Large Language Models (LLMs), Multimodal Models, and custom-trained ML models into enterprise systems.
• Define and implement end-to-end AI solution architectures — from data ingestion, vectorization, and storage to model orchestration, inference APIs, and integration with business workflows.
• Hands-on experience with RAG (Retrieval-Augmented Generation) architectures, including vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma) and embedding pipelines.
• Deep understanding of Model Context Protocol (MCP) and modern AI agent frameworks, ensuring interoperability and modular AI service composition.
• Build and operationalize LLM pipelines using LangChain, LlamaIndex, Semantic Kernel, or Haystack, and integrate with cloud AI services (AWS Bedrock, Azure OpenAI, Google Vertex AI).
• Lead initiatives in AI system modernization, refactoring existing applications to integrate AI capabilities.
• Ensure MLOps practices are implemented across model lifecycle management — versioning, deployment, monitoring, and retraining using MLflow, Kubeflow, or SageMaker pipelines.
• Provide technical direction in selecting the right AI tools, frameworks, and deployment strategies to align with enterprise scalability and compliance requirements.
• Maintain awareness of the rapidly evolving AI ecosystem, evaluating new frameworks, open models (Llama, Mistral, Falcon, etc.), and emerging trends in GenAI and MCP.
• Ensure AI governance, data privacy, model security, and responsible AI practices are embedded in solution delivery.
• Proficiency in LLMOps and model lifecycle management, including CI/CD pipelines for training, testing, and deploying AI models at scale.
• Security, Privacy, and Compliance knowledge, with an understanding of data governance (GDPR, HIPAA, SOC 2) and secure model serving.
• Lead workshops and design sessions to define and refine generative AI solutions focused on LLMs and RAG workflows and l ead the training and optimization of Large Language Models 

  Your Managerial Responsibilities:

• • Lead a cross-functional team of AI engineers, data scientists, and software developers to design and deliver enterprise-grade AI solutions.
  • Translate business goals into technical AI roadmaps and guide the architecture and engineering decisions to achieve them.
  • Review project designs, code, and architecture to ensure performance, maintainability, and adherence to best practices.
  • Oversee project scheduling, budgeting, and resource management while ensuring timely delivery and quality.
  • Act as a trusted advisor to client leadership on AI strategy, implementation approach, and technology selection.
  • Establish AI architecture standards and reference models for reuse across engagements.
  • Build internal capabilities through knowledge-sharing sessions, POCs, and internal accelerator initiatives.
  • Foster collaboration with ecosystem partners (OpenAI, Hugging Face, NVIDIA, Databricks, etc.) for solution innovation.
• Provide mentorship to engineering teams, fostering expertise in AI and software architecture.
• Document architectural designs, workflows, and decisions for transparency and scalability.
• Collaborate with stakeholders to define business requirements and technical specifications for generative AI applications.
• Drive FinOps practices for AI workloads, ensuring cost optimization, budgeting, and governance across multi-cloud environments while maintaining performance and scalability of AI solutions.
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 Your People Responsibilities:

• • Foster teamwork and lead by example, nurturing a culture of continuous learning and innovation in AI technologies.
  • Mentor and coach engineers and data scientists to strengthen hands-on expertise in GenAI frameworks and architectural patterns.
  • Participate in organization-wide AI competency-building initiatives, technical workshops, and internal communities of practice.
  • Possess excellent communication and presentation skills — comfortable representing the organization at client meetings, tech conferences, and leadership reviews.

Requirements (Qualifications):

Education:

• BE/BTech/MCA with 12–18 years of experience, including at least 3–5 years of AI/ML/GenAI architecture and delivery experience.

Mandatory Skills:

• Programming & Frameworks: Python (preferred), Java , FastAPI/Flask, LangChain, LlamaIndex, Semantic Kernel, Haystack
• AI/ML Expertise: Experience with LLMs (GPT, Claude, Llama, Mistral), fine-tuning, prompt engineering, embeddings, vector search
• Architectural Experience: RAG design, Model Context Protocol (MCP), multi-agent system design, microservices integration
• Cloud AI Platforms: AWS Bedrock, Azure OpenAI, GCP Vertex AI
• Data & Storage: SQL/NoSQL (MySQL, MongoDB), Vector Databases (Pinecone, FAISS, Weaviate), Redis
• MLOps & Deployment: Docker, Kubernetes, MLflow, Kubeflow, CI/CD pipelines, monitoring (ELK/Splunk/Prometheus)
• Security & Compliance: OAuth/SAML, data governance, model safety and observability frameworks
• Version Control & Collaboration: Git/GitHub, Jira, Confluence

Preferred Skills:

• Experience with multi-modal AI (text, image, speech integration)
• Knowledge of transformer architecture internals, quantization, and fine-tuning optimization
• Familiarity with AI-driven software agents using LangGraph or CrewAI
• Exposure to BPM tools (Camunda) or workflow orchestration frameworks (Airflow, Prefect)
• Experience in Agile/Scrum/SAFe methodologies
• Contributions to open-source AI projects or participation in AI research/innovation initiatives

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.