Enterprise Architect

EXL; India; Presencial; INR 3.000.000 - 6.000.000; Jornada completa

Descripción de la vacante

EXL is seeking an experienced AI Solutions Architect to design, develop, and implement enterprise-grade AI solutions. The role focuses on Generative AI, Agentic AI, and Retrieval-Augmented Generation (RAG) to solve complex business challenges and accelerate AI adoption across the organization.

The ideal candidate will collaborate with product, business and engineering teams to deliver scalable AI applications, implement governance, and drive MLOps and CI/CD practices for production-ready

Formación

• Bachelor's or Master's degree in Computer Science, AI, ML, or related field.
• Hands-on experience deploying GenAI solutions in production.

Responsabilidades

• Design end-to-end AI solutions using LLMs, Agentic AI and RAG architectures.
• Build autonomous AI agents capable of planning, reasoning, tool usage, and multi-step task execution.
• Develop intelligent apps using LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel or similar.
• Design and optimize RAG pipelines using vector databases and enterprise data sources.
• Integrate AI agents with APIs, databases, enterprise systems and cloud platforms.
• Architect scalable, secure, production-ready AI solutions and governance.

Conocimientos

Agentic AI Architecture

RAG

Prompt Engineering

Multi-Agent Systems

AI Reasoning

Educación

Bachelor's or Master's in CS/AI

Herramientas

LangGraph

LangChain

CrewAI

AutoGen

Semantic Kernel

Descripción del empleo

We are seeking an experienced AI Solutions Architect to design, develop, and implement enterprise-grade AI solutions leveraging Generative AI, Agentic AI, and Retrieval-Augmented Generation (RAG) frameworks. The ideal candidate will work closely with business stakeholders, product teams, and engineering teams to build scalable AI applications that solve complex business challenges and accelerate AI adoption across the organization.

Key Responsibilities

• Design and implement end-to-end AI solutions using LLMs, Agentic AI frameworks, and RAG architectures.
• Build autonomous AI agents capable of planning, reasoning, tool usage, and multi-step task execution.
• Develop intelligent applications using frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, or similar.
• Design and optimize RAG pipelines using vector databases and enterprise data sources.
• Integrate AI agents with APIs, databases, enterprise systems, and cloud platforms.
• Architect scalable, secure, and production-ready AI solutions.
• Collaborate with business and technical teams to translate business requirements into AI-driven solutions.
• Evaluate emerging AI technologies and recommend best-fit architectures.
• Implement monitoring, evaluation, guardrails, and governance for GenAI applications.
• Drive AI solution deployment using MLOps and CI/CD best practices.

Must-Have Skills

Core AI Skills

• Agentic AI Architecture (Mandatory)
• Retrieval-Augmented Generation (RAG) (Mandatory)
• Prompt Engineering & AI Orchestration
• Multi-Agent Systems
• AI Reasoning & Workflow Automation

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related fields.
• Experience deploying GenAI solutions in production environments.
• Hands-on experience with enterprise knowledge management systems and AI-powered assistants.
• Knowledge of Responsible AI, AI Governance, and Security best practices.
• Experience building conversational AI, copilots, AI agents, or workflow automation platforms.

Success Metrics

• Successful deployment of enterprise AI solutions.
• Improved automation and business productivity through AI agents.
• High-performing RAG systems with optimized retrieval accuracy.
• Scalable and secure AI architectures aligned with business objectives.