Gen AI Lead/ Architect

Job description

**Job Title:** Gen AI Lead/ Architect **City:** Bengaluru **State/Province:** Karnataka **Posting Start Date:** 8/5/26 **Wipro Limited (NYSE:** WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com. Role Purpose The purpose of the role is to liaison and bridging the gap between customer and Wipro delivery team to comprehend and analyze customer requirements and articulating aptly to delivery teams thereby, ensuring right solutioning to the customer. ͏ **Gen AI JD for ChevronJD:** Role Overview We are looking for a highly skilled AI Engineer specializing in Generative AI and Multi-Agent Systems to design and deploy intelligent, autonomous solutions. This role focuses on building LLM-powered, agent-driven architectures that can reason, collaborate, and execute complex workflows across enterprise systems. You will work on cutting-edge Agentic AI frameworks, enabling systems that go beyond prediction to decision-making, orchestration, and autonomous execution. Key Responsibilities - Design and build multi-agent AI systems capable of planning, reasoning, and task execution - Develop applications using LLMs (GPT, Claude, Llama, etc.) with advanced prompt engineering and orchestration - Implement Agentic workflows (planner executor critic memory loops) - Build RAG (Retrieval-Augmented Generation) pipelines with vector databases for enterprise knowledge grounding - Develop tool-using agents that integrate with APIs, databases, and enterprise systems - Architect and deploy AI copilots and autonomous assistants for business workflows - Optimize LLM performance using fine-tuning, prompt chaining, and caching strategies - Implement short-term and long-term memory mechanisms (vector stores, knowledge graphs) - Design multi-agent collaboration protocols (hierarchical, swarm, role-based agents) - Deploy scalable solutions using MLOps + LLMOps practices (monitoring, evaluation, guardrails) - Ensure AI safety, governance, and responsible AI practices Required Skills & Qualifications - Bachelor’s/Master’s in Computer Science, AI, or related field - 3–8 years experience in AI/ML with strong focus on Generative AI - Strong Python development skills - Hands-on experience with: **o LLMs & GenAI frameworks:** OpenAI, Hugging Face Transformers **o Agent frameworks:** LangChain, AutoGen, CrewAI, Semantic Kernel **o RAG pipelines & vector DBs:** FAISS, Pinecone, Weaviate - Experience building API-driven, tool-integrated AI agents - Strong understanding of: o Prompt engineering & prompt optimization o Chain-of-thought reasoning and tool augmentation o Context management and token optimization - Experience with cloud platforms (Azure OpenAI preferred, AWS/GCP acceptable) - Knowledge of Docker, Kubernetes, CI/CD pipelines Preferred Qualifications - Experience building multi-agent orchestration systems with role-based coordination - Exposure to agent planning algorithms (ReAct, Plan-and-Execute, Tree-of-Thought) - Experience with LLM evaluation frameworks (RAGAS, TruLens, Promptfoo) - Knowledge of graph-based reasoning / knowledge graphs - Building autonomous systems or copilots in enterprise environments - Domain experience in industrial, energy, or IoT environments Key Competencies - Systems thinking for designing autonomous AI architectures - Strong problem decomposition for agent task design - Ability to balance latency, cost, and accuracy in LLM systems - Communication with business stakeholders to translate workflows into agent pipelines - Innovation mindset with focus on applying agentic AI in production Tech Stack (Modern GenAI Stack) - Languages: Python - Frameworks: LangChain, CrewAI, AutoGen, Semantic Kernel - LLMs: OpenAI GPT, Azure OpenAI, Claude, Llama • ͏ 2. Engage with delivery team to ensure right solution is proposed to the customer **a. Periodic cadence with delivery team to:** Provide them with customer feedback/ inputs on the proposed solution Review the test cases to check 100% coverage of customer requirements Conduct root cause analysis to understand the proposed solution/ demo/ prototype before sharing it with the customer Deploy and facilitate new change requests to cater to customer needs and requirements Support QA team with periodic testing to ensure solutions meet the needs of businesses by giving timely inputs/feedback Conduct Integration Testing and User Acceptance demo’s testing to validate implemented solutions and ensure 100% success rate Use data modelling practices to analyze the findings and design, develop improvements and changes Ensure 100% utilization by studying systems capabilities and understanding business specifications Stitch the entire response/ solution proposed to the RFP/ RFI before its presented to the customer b. Support Project Manager/ Delivery Team in delivering the solution to the customer Define and plan project milestones, phases and different elements involved in the project along with the principal consultant Drive and challenge the presumptions of delivery teams on how will they successfully execute their plans Ensure Customer Satisfaction through quality deliverable on time ͏ 3. Build domain expertise and contribute to knowledge repository Engage and interact with other BA’s to share expertise and increase domain k