Job Summary

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 contemporary 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.

📌 EY - GDS Consulting - AIA - AI Archictect- Manager (Chennai)
🏢 EY
📍 Chennai