EY - GDS Consulting - AIA - AI Archictect- Manager
EY · Chennai
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.
AI Architect
Enterprise GenAI, Agentic AI and AI Platform Architecture
Career Family AIA - AI / GenAI / Agentic AI
Role Type Full Time
The opportunity
We are seeking an experienced AI Architect to lead the design and delivery of secure, scalable and production-ready enterprise AI solutions. The role combines hands-on architecture with consulting leadership across Generative AI, Agentic AI, retrieval-augmented generation (RAG), AI/ML, cloud platforms and modern application engineering. The architect will translate business priorities into target-state architectures, reusable patterns and implementation roadmaps while guiding multidisciplinary teams from discovery through deployment and operationalization.
The ideal candidate has delivered enterprise or client-facing AI solutions in pre-production or production environments and can explain the use case, architecture, personal contribution, controls, delivery approach and outcomes. Certifications, personal projects and demonstrations alone are not sufficient.
Your key responsibilities
- Lead discovery and architecture workshops, clarify business outcomes and non-functional requirements, and convert them into scalable AI solution designs and delivery roadmaps.
- Architect LLM applications, copilots, RAG and Graph RAG solutions, autonomous agents, multi-agent workflows, tool/function calling, memory patterns and human-in-the-loop controls.
- Define reference architectures and reusable patterns for document ingestion, chunking, embeddings, vector and hybrid search, grounding, prompt workflows, model routing and enterprise integrations.
- Select fit-for-purpose models, cloud services, vector stores, orchestration frameworks and evaluation approaches based on security, quality, latency, cost, scalability and maintainability requirements.
- Design API-first, event-driven and microservices-based integrations with enterprise applications, data platforms, workflow systems and user experience layers.
- Establish AI evaluation and observability covering retrieval quality, groundedness, accuracy, hallucination risk, agent trajectories, tool execution, latency, cost and user experience.
- Embed Responsible AI, privacy, security and compliance controls including PII protection, access control, auditability, prompt-injection mitigation, content safety, secure tool execution and data-leakage prevention.
- Define cloud-native deployment and operations patterns using containers, Kubernetes or managed services, CI/CD, infrastructure as code, model/LLM operations, monitoring and release controls.
- Lead architecture reviews, technical design reviews, code reviews and production-readiness assessments; troubleshoot complex issues and guide performance optimization.
- Partner with business stakeholders, product owners, data scientists, engineers, UX teams, security and platform teams to ensure alignment from design through adoption.
- Contribute to proposals, RFP responses, estimates, executive presentations, accelerators, reusable assets and AI practice development.
- Lead and mentor architects and engineers, promote engineering standards, and build capability through coaching and knowledge sharing.
Skills and attributes
Professional experience
- 10+ years of experience in AI, data, analytics, software engineering or digital transformation, including significant responsibility for solution architecture and end-to-end delivery.
- Strong hands-on experience designing and deploying enterprise-scale AI/ML, GenAI, RAG or Agentic AI solutions in client-facing environments.
- Proven experience leading cross-functional teams, architecture governance, stakeholder engagement and complex delivery programs.
- Ability to communicate architecture decisions, trade-offs and business value to technical and executive audiences.
Technical skills
- Deep understanding of LLMs, prompt engineering, RAG, Graph RAG, Agentic RAG, embeddings, vector and hybrid search, knowledge graphs, model evaluation and fine-tuning approaches.
- Hands-on experience with agent frameworks such as Microsoft Agent Framework, LangGraph, LangChain, AutoGen, CrewAI or Google Agent SDK, and familiarity with Model Context Protocol (MCP).
- Strong experience with at least one enterprise cloud AI ecosystem: Microsoft Azure AI Foundry and Azure OpenAI; AWS Bedrock; or GCP Vertex AI and Gemini. Multi-cloud exposure is preferred.
- Experience with data and AI platforms such as Databricks, Azure AI Search, Microsoft Fabric, Synapse, BigQuery or equivalent enterprise data services.
- Strong proficiency in Python and SQL; working knowledge of REST APIs, FastAPI, JSON, asynchronous processing, microservices and event-driven architecture.
- Experience with vector databases, enterprise search, relational and NoSQL data stores, caching and analytics stores.
- Understanding of ML, deep learning, NLP, predictive analytics and the end-to-end AI lifecycle.
- Experience with Docker, Kubernetes or OpenShift, Git, CI/CD, automated testing, infrastructure as code, MLOps, LLMOps, observability and production support.
- Strong knowledge of enterprise architecture, data governance, model risk, Responsible AI, privacy, cybersecurity, accessibility and regulatory controls.
Consulting and leadership skills
- Strong client engagement, workshop facilitation, stakeholder management, presentation and executive communication skills.
- Ability to translate complex business requirements into practical, high-quality technical architectures and phased implementation plans.
- Leadership in solution estimation, delivery governance, risk management, quality assurance, mentoring and capability building.
- Curiosity, structured problem-solving, commercial awareness and commitment to continuous learning.
Education and preferred certifications
- Bachelor's or master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Mathematics, Statistics or a related quantitative discipline.
- Relevant certifications in Azure AI, AWS, Google Cloud, Databricks, AI/ML, Generative AI or enterprise architecture are preferred.
Why join us
- Be at the forefront of AI-driven innovation across multiple client sectors.
- Work with global clients to deliver measurable business impact.
- Collaborate with AI experts, analytics leaders and industry specialists in a highly entrepreneurial environment.
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.
- Continuous learning: You will develop the mindset and skills to navigate whatever comes next.
- Success as defined by you: We provide the tools and flexibility so you can make a meaningful impact, your way.
- Transformative leadership: We provide insights, coaching and confidence to help you become the leader the world needs.
- Diverse and inclusive culture: You will be empowered to use your voice and help others find theirs.
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