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 Tech Lead – AI, Agentic & GenAI Delivery Role Type - RDE Tech Lead – AI, Agentic & GenAI Delivery Role Title - RDE Senior Tech Lead / Delivery Co-Lead 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 Level 6 Senior Tech Lead / Delivery Co-Lead will be responsible for senior delivery governance and co-leadership across enterprise AI delivery programs. The role will support cloud-native architecture, LLM implementation, cross-workstream governance, and AI delivery co-leadership for Agentic AI and GenAI solutions. Primary Focus - Agentic AI leadership, GenAI/LLM strategy, technical delivery governance, cloud/platform architecture, and stakeholder/client management. Must Have Experience:

Lead the end-to-end technical delivery of Agentic AI solutions.
Drive/knowledge the implementation of Agentic AI frameworks and technologies. What are we looking for
Agentic AI Leadership - Agent Architecture Design, Multi-Agent Frameworks, Agent Orchestration & Workflow Design, Tool Calling & Integration Patterns, AI Solution Delivery Leadership
GenAI & LLM Skills - Large Language Models (GPT, Claude, Gemini, Llama), Prompt Engineering & Optimization, Retrieval Augmented Generation (RAG), Vector Databases and Semantic Search, Responsible AI and Governance Practices
Delivery Governance - Solution Architecture Reviews - Code Quality and Development Standards, Agile Delivery and Sprint Management, Risk and Dependency Management, Technical Design Governance
Cloud & Platform Architecture - Azure, AWS, or GCP Cloud Platforms, Microservices and Distributed Systems, Docker and Kubernetes, API Management and Integration, CI/CD and DevSecOps Practices
Stakeholder Management - Client Relationship Management, Business Requirement Translation, Executive Communication and Reporting, Escalation Management, Roadmap Planning and Delivery Tracking
Professional Skills - Strategic Problem Solving, Leadership and Team Management, Cross-Functional Collaboration, Presentation and Communication Skills, Mentoring and Capability Development
Enterprise AI delivery and GenAI implementation
Agentic AI architecture and multi-agent systems
LLM strategy, RAG architecture, vector databases, and prompt engineering
Technical governance across multiple delivery workstreams
Cloud-native architecture across AWS, Azure, or GCP
DevSecOps, CI/CD, microservices, containers, and API gateway
Client delivery, escalation management, and roadmap translation
Design reviews, sprint governance, delivery quality, and risk management Roles and Responsibilities:
Lead end-to-end delivery of enterprise Agentic AI and GenAI solutions.
Govern technical delivery across workstreams, including code quality, architecture compliance, sprint velocity, design reviews, and risk management.
Support LLM selection, prompt engineering standards, RAG architecture, vector database strategy, and Responsible AI guardrails.
Provide technical leadership for agent architecture, orchestration strategy, tool-calling patterns, and multi-agent coordination frameworks
Define and support cloud-native deployment strategies across AWS, Azure, or GCP.
Drive implementation standards around microservices, containers, API gateway, CI/CD, DevSecOps, and production AI deployment.
Engage with client stakeholders, manage escalations, translate business requirements into delivery roadmaps, and report solution progress.