AI LLM Technology Architecture Manager

Skill required: Tech for Operations - Artificial Intelligence (AI)
Designation: AI LLM Technology Architecture Manager
Qualifications:BE/BTech/MTech
Years of Experience:12 to 16 years
Language - Ability:English(International) - Intermediate
About Accenture
Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song— all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 784,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com
What would you do? Level 7 - RDE Technical Architect – AI, Agentic & GenAI Platform Role Type - RDE Technical Architect – AI, Agentic & GenAI Platform Role Title - RDE Technical Architect Reinvention Deployment Engineering (RDE) - is an approach used by Accenture to reimagine and accelerate the delivery of engineering and R&D solutions. It focuses on combining human expertise with AI-driven agents to enhance innovation velocity, streamline processes, and reduce time to market for products and services. RDE emphasizes a value-driven mindset, where humans define objectives and ethical guardrails while AI agents handle scale, speed, and data-driven execution Role Purpose: The Technical Architect will independently design and deliver enterprise AI platform solutions and Agentic AI architectures. The role focuses on defining architecture patterns, guiding engineering teams, and ensuring scalable, secure, and production-ready AI implementations. Primary Focus - Agentic AI architecture, enterprise AI platform design, integration/data architecture, security/compliance, Responsible AI, and reusable solution blueprinting. Must Have Experience: • Lead the architecture, design, and delivery of enterprise-scale Agentic AI solutions
What are we looking for? •Required skills: • Agentic AI Architecture -Agent Architecture Design, Multi-Agent Systems and Coordination, Agent Memory and Context Management, Agent Orchestration & Workflow Design, Tool Integration and Failover Strategies • Enterprise AI Platform Design - Vector Databases and Semantic Search, Embeddings and Retrieval Frameworks, LLM Gateway and Model Routing, AI Inference Optimization, AI Cost Governance and Monitoring, Enterprise AI Platform Architecture • Integration & Data Architecture - SAP, Salesforce, ServiceNow, and Appian Integration, API Architecture and Contract Design, Event-Driven Architecture, Kafka/MSK and Streaming Platforms, Data Architecture and Security Design, Enterprise Integration Patterns • Security & Responsible AI - OAuth and Identity Management, Azure AD / Enterprise Authentication, Responsible AI Guardrails, Bias Detection and Risk Mitigation, Audit Logging and Traceability, GDPR, SOX, and Regulatory Compliance, Data Privacy and Sovereignty Management • Reusable Blueprinting - Enterprise Reference Architectures, Reusable AI Solution Patterns, Platform Standards and Governance, Scalable AI Design Frameworks, Architecture Best Practices and Guidelines, Enterprise AI Modernization Strategies Required Skills : • Professional Skills - Solution Architecture and Technical Leadership, Strategic Problem Solving, Cross-Functional Collaboration, Stakeholder and Client Engagement, Communication and Presentation Skills, Team Leadership and Mentoring, Innovation and Continuous Improvement Technology Advisory and Decision Making
Roles and Responsibilities: • Design end-to-end Agentic AI solutions including agent topology, memory and context management, orchestration frameworks, and tool integrations. • Build AI platform architectures leveraging vector stores, embedding pipelines, model routing, LLM gateways, and inference optimization. • Define integration architectures across enterprise platforms including SAP, Salesforce, ServiceNow, and Appian. • Implement security, Responsible AI, compliance, and governance controls. • Create reusable architecture patterns, solution blueprints, and technical standards. • Provide hands-on technical guidance to engineering and delivery teams. • Support scalable deployment of AI and GenAI solutions across client environment