AI Software Engineer (Agentic AI & MCP Systems)

Sutherland is hiring an AI Software Engineer (Agentic AI & MCP Systems) to join their team in Bengaluru. This is a permanent Work At Home position. The role involves designing scalable AI systems, developing intelligent agents, implementing Retrieval-Augmented Generation (RAG) pipelines, and building enterprise-grade AI applications powered by modern cloud technologies such as AWS Bedrock. The ideal candidate should have strong development experience in Python and/or TypeScript, hands-on experience building MCP Servers or similar LLM integration layers, and experience with AI agent frameworks such as LangGraph, LangChain, and CrewAI. You will work on designing next-generation systems capable of planning, reasoning, and executing complex workflows through modern LLM architectures. Sutherland is a global leader in digital transformation and business process excellence, with more than 200 patented inventions across AI and emerging technologies.

Design, develop, and maintain MCP servers using Python and/or TypeScript. Build scalable AI systems capable of multi-step planning, reasoning, and execution. Develop intelligent agent workflows with tool/function calling capabilities. Implement short-term and long-term memory management for AI agents. Build context-aware execution pipelines with appropriate guardrails. Design Retrieval-Augmented Generation (RAG) pipelines including document ingestion, chunking strategies, embedding generation, vector storage, and hybrid retrieval mechanisms. Implement Graph RAG and Knowledge Graph-based reasoning solutions. Deploy AI systems using AWS Bedrock and related AWS cloud services. Follow Software Development Life Cycle (SDLC) best practices. Write clean, modular, maintainable, and well-documented code. Participate in architecture discussions and peer code reviews.

Strong development experience in Python and/or TypeScript. Hands-on experience building MCP Servers or similar LLM integration layers. Experience with AI agent frameworks such as LangGraph, LangChain, and CrewAI. Experience using AI-powered developer tools including GitHub Copilot, Cursor, Windsurf, Claude Code, Kiro, or similar AI coding assistants. Experience designing AI systems on AWS Cloud, particularly AWS Bedrock. Strong understanding of Large Language Models (LLMs), Prompt Engineering, Tool Usage, Memory Management, and AI Orchestration. Practical experience with Vector Databases, Embeddings, Retrieval-Augmented Generation (RAG), and RAG Optimization. Strong software engineering fundamentals. Experience with REST APIs and Microservices. Familiarity with Git workflows and CI/CD pipelines.