Highlights:
12.00 – 18.00 Years
26.00 – 45.00 INR (Lacs)/Yearly
Full-time
Pan india
Skills
AI
Roles & Responsibility
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
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
Professional 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.
BE,BTech,MTech
