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From staff augmentation to dedicated IT teams and general software engineering, our nearshore technology services empower businesses to thrive in anever-evolving digital landscape\nAbout the Role\nAs an Agentic AI Developer, you will serve as the technical backbone of our AI engineering PODs, designing, building, and deploying production-ready AI agents and agentic workflows. You will focus on orchestrating autonomous systems using leading LLM frameworks, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP) to seamlessly connect AI capabilities with client software ecosystems and enterprise data sources.\nThis role is critical to transforming business requirements into scalable, secure, and reliable agentic AI solutions on AWS. 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exposure.\n\nDeploy & Monitor: Deploy LLM applications on AWS utilizing Amazon Bedrock, while leveraging observability platforms such as LangSmith, Langtrace, or AgentOps to troubleshoot failures and optimize performance.\n\nCollaborate & Maintain: Write clean, maintainable, and testable Python code, maintaining comprehensive technical documentation while collaborating with senior engineers, MLOps, and product teams.\n\nRequirements\nExperience: 3+ years of professional software development experience, with direct, hands-on experience building LLM-based, RAG, or agentic AI applications.\n\nTech Stack: Advanced Python, AWS (Amazon Bedrock), agentic frameworks (LangGraph, CrewAI, or ADK), Vector DBs (Pinecone, Weaviate), and Model Context Protocol (MCP).\n\nObservability & Testing: Hands-on experience testing, evaluating, and monitoring LLM execution using tools like LangSmith, Langtrace, or AgentOps.\n\nSoft Skills: Ownership mindset, strong troubleshooting capabilities, and a 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