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

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at www.accenture.com

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