17 hours ago
Chennai, IndiaStaff+
Responsibilities
- Define enterprise AI strategy, target-state architecture, investment roadmaps, reference architectures, and implementation sequencing.
- Architect and integrate Azure AI and LLM platforms using Azure AI Foundry, Azure OpenAI, Azure AI Search, Prompt Flow, Azure Functions, Logic Apps, API Management, and related services.
- Lead architecture for agentic systems, orchestration, memory, tool use, agent registries, AI gateways, control planes, context layers, knowledge graphs, vector search, and semantic retrieval.
- Establish identity, authorization, guardrails, prompt-injection defense, PII protection, audit logging, lineage, responsible AI, and defense-in-depth controls.
- Define evaluation, observability, reliability, safety, latency, quality, production support, and continuous-improvement practices for AI systems.
- Establish AI FinOps practices covering usage labeling, token budgets, cost planning, threshold alerts, and optimization.
- Lead domain architects and senior SMEs and advise executive stakeholders on enterprise AI transformation and technology investments.
- Produce authoritative architecture assets including AI blueprints, ADRs, sequence diagrams, solution patterns, interface specifications, reference architectures, and governance playbooks.
Requirements
- Bachelor's degree or equivalent in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline.
- At least 15 years of overall experience across software engineering, data engineering, AI/ML engineering, cloud architecture, enterprise architecture, or technology leadership.
- At least 8 years designing and deploying enterprise-grade AI, data, analytics, or cloud-native solutions using at least one cloud vendor.
- At least 2 years of experience with LLM and generative AI solution architecture, including agentic systems, RAG, prompt engineering, model integration, and evaluation.
- At least 2 years architecting and operationalizing LLM-driven application patterns in enterprise-scale or production environments.
- At least 6 years of experience in engineering, machine learning, deep learning, NLP, data engineering, or large-scale analytical engineering.
- At least 6 years as a machine learning, data, or AI architect designing large-scale analytical engineering solutions in industry contexts.
- Deep experience with Azure AI Foundry, Foundry Agent Service, Azure OpenAI models, Azure AI Search, Prompt Flow, Azure Functions, Logic Apps, API Management, Event Grid, Microsoft Fabric, Entra ID, Key Vault, Azure Monitor, and Application Insights.
- Expertise in RAG, embeddings, vector databases, semantic retrieval, context engineering, model routing, agent orchestration, memory, tool calling, AI gateways, and model evaluation.
- Experience defining enterprise non-functional requirements, architectural controls, design patterns, reference architectures, technology selections, foundation models, and deployment approaches.
- Experience establishing agent registries, certification models, AI control planes, access models, guardrails, evaluation stacks, model risk controls, and cross-platform governance.
- Strong executive communication, architecture governance, influence, and thought leadership skills.
- Preferred experience includes Azure Solutions Architect Expert, Azure AI Engineer Associate, or Azure Developer certifications; Microsoft Fabric, Semantic Kernel, Prompt Flow, private endpoints, Defender for Cloud, Microsoft 365 Copilot extensibility, responsible AI governance, and enterprise integration patterns.
- Exposure to LangChain, LangGraph, LlamaIndex, Haystack, Semantic Kernel, MLflow, FastAPI, Docker, and Kubernetes is preferred.
- Experience with responsible AI, model risk management, AI governance boards, red-teaming, synthetic data, human-in-the-loop review, A/B testing, or GenAI FinOps is preferred.
Tech Stack
Categories
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.