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 Tech Lead – AI, Agentic & GenAI Delivery Role Type - RDE Tech Lead – AI, Agentic & GenAI Delivery Role Title - RDE Tech Lead / Delivery 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 7 Tech Lead / Delivery Lead will lead hands-on delivery across Agentic AI and GenAI programs, with ownership of AI delivery at POD or workstream level.

This role will guide technical teams,



ensure architecture compliance, and support client-facing execution for production-grade AI 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 & GenAI Leadership

Agent Architecture & Multi-Agent Systems, Agent Orchestration and Workflow Automation, Tool Calling & AI Integration Frameworks, Large Language Models (GPT, Claude, Gemini, Llama), Prompt Engineering, RAG, and Vector Databases, Responsible AI and AI Governance Solution & Delivery Leadership

AI Solution Architecture and Design Reviews, Agile Delivery and Program Governance, Code Quality and Engineering Best Practices, Risk, Issue, and Dependency Management, Technical Leadership and Decision Making Cloud & Platform Engineering

Azure, AWS, and GCP Cloud Platforms, Microservices and Distributed Architectures, Docker, Kubernetes, and Containerization, API Integration and Platform Engineering, CI/CD, DevSecOps, and Production Deployment Stakeholder & Client Management

Executive and Client Engagement, Business Requirements Translation, Escalation and Delivery Governance, Roadmap Planning and Progress Reporting,



Cross-Functional Collaboration Qualified Skills

Strategic Thinking and Problem Solving, Team Leadership and People Development, Communication and Presentation Skills, Mentoring and Capability Building, Innovation and Continuous Improvement.

Agentic AI delivery and GenAI solution implementation

LLMs, prompt engineering, RAG architecture, vector databases, and Responsible AI

AI technical delivery leadership at POD or workstream level

Cloud AI delivery across AWS, Azure, or GCP

Microservices, containerization, API gateway, CI/CD, and DevSecOps

Architecture compliance, code quality, sprint tracking, and risk management

Client stakeholder coordination and solution progress reporting

Team guidance and hands-on technical delivery management Roles and Responsibilities:

Lead delivery of Agentic AI and GenAI solutions at POD or workstream level.

Support end-to-end design of AI solutions, including agent architecture, orchestration strategy, tool-calling patterns, and multi-agent coordination.

Drive implementation of LLM selection, prompt engineering standards, RAG architecture, vector database strategy, and Responsible AI guardrails.

Ensure code quality, architecture compliance, design review participation, sprint velocity tracking, and delivery risk management.

Support cloud deployment across AWS, Azure, or GCP, including microservices, containerization, API gateway, CI/CD, and DevSecOps practices.

Work with client stakeholders to understand requirements, convert business needs into technical roadmaps, and provide solution progress updates.

Guide and mentor technical teams to deliver scalable, production-ready AI solutions with quality and speed.

📌 AI LLM Technology Architecture Manager (Bengaluru)
🏢 Accenture in India
📍 Bengaluru