AI Architect-Manager
Job description
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.
Career Family
EY-DET-FS
Role Type
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 architectures. You will work at the intersection of cloud-native systems, large language models (LLMs), multimodal AI, and Retrieval-Augmented Generation (RAG) 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.
- Collaborate with cloud and DevOps teams to establish CI/CD pipelines for AI workloads, containerized via Docker/Kubernetes.
- 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.
Your Managerial Responsibilities:
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- 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.
Your People Responsibilities:
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- 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.
EY | Building a better working world
EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.
Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.
Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.