Tech Architecture Sr Manager

Tech Architecture Sr Manager

Skill required: Tech for Operations - Artificial Intelligence (AI)
Designation: Tech Architecture Sr Manager
Qualifications:BE/BTech/MTech
Years of Experience:15 to 18 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 6 – RDE Technical Architect – AI, Agentic & GenAI Platform Role Type - RDE Technical Architect – AI, Agentic & GenAI Platform Role Title - RDE Senior 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 Senior Technical Architect will provide strategic architecture leadership for enterprise AI platforms and Agentic AI solutions. The role is responsible for cross-platform architecture design, security and compliance governance, and oversight of multiple AI transformation initiatives. 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 & Enterprise Architecture -Agent Architecture & Multi-Agent Systems, Agent Orchestration, Memory, and Context Management, Tool Integration and AI Workflow Design, Enterprise AI Solution Architecture,Scalable and Resilient AI Platform Design • Enterprise AI Platform & GenAI - Large Language Models (LLMs) and AI Platform Strategy, RAG, Embeddings, and Vector Databases, LLM Gateway and Model Routing, AI Inference Optimization, AI Cost Governance and Performance Management • Integration & Data Architecture - SAP, Salesforce, ServiceNow, and Appian Integrations, API Architecture and Contract Design, Event-Driven Architecture and Kafka/MSK, Enterprise Data Architecture, Data Security and Integration Governance • Security & Responsible AI - OAuth, Azure AD, and Identity Management, Responsible AI Guardrails, Data Privacy and Sovereignty, Bias Detection and Risk Management, Audit Logging, SOX, GDPR, and Regulatory Compliance • Architecture Governance & Blueprinting - Reference Architecture Development, Reusable AI Solution Patterns, Platform Standards and Governance, Scalable Enterprise AI Frameworks, Architecture Reviews and Design Best Practice. Required Skills: • Leadership & Stakeholder Management - Client and Executive Stakeholder Engagement, Technology Strategy and Roadmap Planning, Solution Governance and Risk Management, Cross-Functional Team Leadership, Mentoring and Capability Development • Professional Skills - Strategic Problem Solving, Innovation and Thought Leadership, Communication and Presentation Skills, Decision Making and Influence, Collaboration and Organizational Leadership
Roles and Responsibilities: • Lead architecture design across multiple AI and GenAI workstreams. • Govern platform standards for agent orchestration, memory management, model integration, and AI scalability. • Define integration and data architecture strategies across enterprise systems. • Ensure adherence to security, regulatory, Responsible AI, and compliance frameworks. • Establish enterprise-wide standards for reusable AI solution blueprints. • Drive architecture reviews, technical governance, and platform optimization initiatives. • Mentor architecture teams and provide oversight across implementation programs. • Collaborate with client stakeholders and leadership teams on AI platform roadmaps.