Role description

Key Responsibilities

Experience: 12-16 Years
Role: AI Architect – Agentic AI & Advanced RAG
Employment Type: Full-Time

AI Architect – Agentic AI, RAG & Multi-Agent Systems About the Role

We are looking for an experienced AI Architect to lead the design and development of enterprise-scale Agentic AI solutions. The ideal candidate will possess deep expertise in AI architecture, multi-agent systems, advanced RAG implementations, and modern AI platforms. This role will drive the creation of scalable, secure, and production-ready AI solutions while providing technical leadership across AI engineering initiatives.

Key Responsibilities

AI Architecture & Solution Design

- Design and architect enterprise-scale Agentic AI solutions leveraging autonomous and collaborative AI agents.
- Define end-to-end architecture for AI applications, including LLMs, RAG pipelines, agent orchestration, tool integration, memory management, and workflow automation.
- Establish architectural patterns and best practices for multi-agent systems, planning agents, reasoning agents, and task orchestration frameworks.
- Drive AI platform modernization initiatives and define reusable frameworks, accelerators, and reference architectures.

Agent Development & Orchestration

- Design, build, and optimize AI agents using frameworks such as LangGraph, LangChain, AutoGen, CrewAI, Google ADK, or equivalent.
- Implement complex multi-agent workflows involving planning, reasoning, task decomposition, collaboration, and human-in-the-loop processes.
- Develop agent communication and orchestration mechanisms using contemporary agentic architecture principles.

Advanced RAG & Knowledge Systems

- Architect and implement advanced RAG solutions using hybrid search, semantic retrieval, graph-based retrieval, agentic retrieval, and contextual memory.
- Design scalable knowledge ingestion, indexing, chunking, embedding, and retrieval pipelines.
- Integrate enterprise knowledge sources including documents, databases, APIs, and knowledge repositories.
- Leverage Knowledge Graphs to enhance contextual understanding and improve agent reasoning capabilities.

AI Platform Engineering

- Develop backend services and APIs using Python and FastAPI.
- Design scalable AI microservices and deploy cloud-native AI solutions.
- Integrate vector databases such as Pinecone, FAISS, ChromaDB,



or equivalent platforms for semantic retrieval.

AI Evaluation, Monitoring & Governance

- Define evaluation frameworks to measure AI system quality, accuracy, relevance, faithfulness, latency, and business outcomes.
- Implement AI evaluation methodologies using RAGAS, DeepEval, LangSmith, or similar tools.
- Establish observability and monitoring practices using solutions such as LangSmith, Langfuse, Arize, or equivalent.
- Collaborate with governance and security teams to ensure responsible AI implementation and compliance.

Technical Leadership

- Provide technical guidance and mentorship to AI engineers and solution architects.
- Conduct architecture reviews, code reviews, and design workshops.
- Collaborate with business stakeholders to translate business requirements into scalable AI solutions.
- Drive innovation by evaluating emerging trends in Agentic AI, LLMOps, AI infrastructure, and autonomous systems.

Required Skills & Qualifications

Technical Expertise

- Strong hands-on development experience in Python.
- Deep expertise in at least two of the following frameworks:
- LangChain
- LangGraph
- AutoGen
- CrewAI
- Google ADK

- Strong experience designing and implementing Agentic AI applications and Multi-Agent Architectures.
- Advanced knowledge of Retrieval-Augmented Generation (RAG) architectures and optimization techniques.
- Expertise in semantic search, embeddings, retrieval techniques, and vector-based architectures.

AI Infrastructure & Platforms

- Hands-on experience with vector databases such as:
- Pinecone
- FAISS
- ChromaDB
- Similar vector search platforms

- Strong understanding of:

- MCP (Model Context Protocol)
- Knowledge Graphs
- Agent memory architectures
- Tool calling and function-calling mechanisms

Evaluation & Observability

- Experience implementing AI evaluation frameworks such as:
- RAGAS
- DeepEval
- LangSmith Evaluations

- Experience with AI observability and LLMOps platforms including:

- LangSmith
- Langfuse
- Arize AI
- Equivalent monitoring tools





API Integration & Development

- Experience building production-grade APIs using FastAPI.
- Strong understanding of REST APIs, API integrations, and enterprise application integration patterns.

Architecture & Design

- Experience designing highly scalable, secure, and resilient AI systems.
- Strong understanding of microservices, distributed systems, and cloud-native architectures.
- Ability to define reference architectures, design patterns, and reusable AI solution components.

Preferred Qualifications
- Experience leading AI architecture and enterprise AI transformation initiatives.
- Exposure to cloud platforms such as Azure, AWS, or GCP.
- Experience with AI governance, security, and responsible AI frameworks.
- Strong stakeholder management and technical leadership skills.

Skills
Mandatory Skills : Architecture Principle Design, Data Architecture, SOA and Microservices Based Architecture, TCO Evaluation, Transformation

About LTM
LTM is an AI-centric global technology services company and the Business Creativity partner to the world’s largest and most disruptive enterprises. We bring human insights and intelligent systems together to help clients create greater value at the intersection of technology and domain expertise. Our capabilities span integrated operations, transformation, and business AI — enabling recent ways of working, new productivity paradigms, and new roads to value. Together with over 87,000 employees across 40 countries and our global network of partners, LTM — a Larsen & Toubro company — owns business outcomes for our clients, helping them not just outperform the market, but to Outcreate it. Please also note that neither LTM nor any of its authorized recruitment agencies/partners charge any candidate registration fee or any other fees from talent (candidates) towards appearing for an interview or securing employment/internship. Candidates shall be solely responsible for verifying the credentials of any agency/consultant that claims to be working with LTM for recruitment. Please note that anyone who relies on the representations made by fraudulent employment agencies does so at their own risk, and LTM disclaims any liability in case of loss or damage suffered as a consequence of the same. Recruitment Fraud Alert - https://www.ltm.com/careers/recruitment-fraud-alert

📌 Associate Principal - Architecture (India)
🏢 LTM
📍 India