EY - GDS Consulting - AIA - AI Archictect- Manager
Ernst and Young8 days ago
Chennai, IndiaStaff+
Responsibilities
- Lead discovery and architecture workshops, define business outcomes and non-functional requirements, and create scalable AI solution designs and delivery roadmaps.
- Architect LLM applications, copilots, RAG and Graph RAG solutions, autonomous agents, multi-agent workflows, tool calling, memory patterns, and human-in-the-loop controls.
- Define reusable architectures for document ingestion, embeddings, vector and hybrid search, grounding, prompt workflows, model routing, and enterprise integrations.
- Select models, cloud services, vector stores, orchestration frameworks, and evaluation approaches based on security, quality, latency, cost, scalability, and maintainability.
- 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 for retrieval quality, groundedness, accuracy, hallucination risk, agent trajectories, tool execution, latency, cost, and user experience.
- Implement Responsible AI, privacy, security, compliance, PII protection, access control, auditability, prompt-injection mitigation, content safety, secure tool execution, and data-leakage prevention controls.
- Define cloud-native deployment and operations patterns using containers, Kubernetes or managed services, CI/CD, infrastructure as code, model operations, monitoring, and release controls.
- Lead architecture reviews, technical design reviews, code reviews, production-readiness assessments, troubleshooting, and performance optimization.
- Partner with business stakeholders, product owners, data scientists, engineers, UX teams, security teams, and platform teams 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 and build technical capability through coaching and knowledge sharing.
Requirements
- 10+ years of professional experience in AI, data, analytics, software engineering, or digital transformation, including significant solution architecture and end-to-end delivery responsibility.
- Hands-on experience designing and deploying enterprise-scale AI/ML, Generative AI, RAG, or Agentic AI solutions in client-facing environments.
- 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.
- 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, plus familiarity with Model Context Protocol.
- 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 Databricks, Azure AI Search, Microsoft Fabric, Synapse, BigQuery, or equivalent enterprise data services.
- Strong proficiency in Python and SQL, with 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 machine learning, 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.
- Knowledge of enterprise architecture, data governance, model risk, Responsible AI, privacy, cybersecurity, accessibility, and regulatory controls.
- Strong client engagement, workshop facilitation, stakeholder management, presentation, executive communication, estimation, delivery governance, risk management, quality assurance, mentoring, and capability-building skills.
- 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.
Benefits
- Opportunity to work at the forefront of AI innovation across multiple client sectors and deliver measurable business impact with global clients.
- Collaboration with AI experts, analytics leaders, and industry specialists in an entrepreneurial environment.
- Continuous learning, coaching, leadership development, and tools and flexibility to make a meaningful impact.
- Inclusive culture that empowers employees to use their voice and help others find theirs.
- Full-time role within EY Global Delivery Services, which operates across Argentina, China, India, the Philippines, Poland, and the UK.
Tech Stack
Categories
Solutions Engineering
About Ernst and Young
Ernst & Young (EY) provides audit/assurance, tax, consulting, strategy and transactions services to enterprises, financial institutions, and public‑sector clients. Structured as a global network of partner‑owned member firms, it sells professional services on a fee basis, including a dedicated Financial Services Organization for banking, insurance, and capital markets. Headquartered in London, EY was formed in 1989 from the merger of Ernst & Whinney and Arthur Young, and operates in 150+ countries.