Data Architect

Project Role : Data Architect Project Role Description : Define the data requirements and structure for the application. Model and design the application data structure, storage and integration. Must have skills : AI Agents & Workflow Integration Good to have skills : NA Minimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Role Overview : As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI systems across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements. Roles & Responsibilities: Design and build production-grade agentic systems end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets Integrate and abstract across multiple LLM providers — OpenAI, Anthropic, Vertex AI, and open-source models — with fallback routing, token, cost, and latency management Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring Embed directly with client engineering teams to design, prototype, and deploy agentic solutions — workshops, proofs of concept, code-with sessions, and architecture walkthroughs Build reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness present findings and recommendations to client stakeholders in business terms. Professional & Technical Skills: Software engineering experience in production environments hands-on experience designing and deploying agentic AI solutions in a production environment — non-negotiable Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent — at production depth, not tutorial level Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering LLMOps fundamentals: eval harness design, prompt versioning, and production observability Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm) Strong Python Java or equivalent backend language acceptable production debugging and observability experience Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure. Additional Information: - The candidate should have minimum 7.5 years of experience in AI Agents & Workflow Integration. - This position is based at our Bengaluru office. - A 15 years full time education is required. Production agentic system shipped, at least one multi-step agentic system in a real environment. Design decisions must be articulable under questioning RAG pipeline ownership: chunking decisions and metric-backed quality tradeoffs explained not 'I used LangChain' Multi-LLM provider integration in production: abstraction layer, fallback routing, cost and latency management across at least two providers Eval harness built and defended: ran an evaluation framework with specific metrics, can defend every number and explain why each was chosen LLMOps in production: prompt versioning, observability tooling, safety monitoring — active use, not awareness Cloud-native maturity: Kubernetes, Docker, serverless, IaC — evidence of delivery ownership. 15 years full time education Important Notice We have been alerted to the existence of fraudulent messages asking job seekers to set up payment to cover various costs associated with establishing employment at Accenture. No one is ever required to pay for employment at Accenture. If you are contacted by someone asking for payment, please do not respond, and contact us at india.fc.check@accenture.com immediately. Equal Employment Opportunity Statement All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Please read Accenture’s Recruiting and Hiring Statement for more information on how we process your data during the Recruiting and Hiring process.