AI Engineer – Agentic AI & Multi-Agent Systems | AWS Bedrock, LangChain & LangGraph
Synechron (company site, opens in a new tab)6+ yrsBengaluruOn-siteDirect career pageEst. 20–32 LPA
Posted 9h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and deploy enterprise-grade autonomous AI agents and multi-agent workflows using frameworks like Amazon Bedrock, AgentCore, LangChain, LangGraph, and Strands Agents SDK.
- Translate business and product requirements into technical designs and measurable AI solutions to improve workflow automation, decision support, operational efficiency, and enable responsible generative AI adoption.
- Collaborate with cross-functional teams for solution design, production deployment, optimization, monitoring, and support of scalable, secure, and reliable AI-driven applications.
Minimum Requirements
- Overall professional experience: Minimum 6 years in software engineering, AI engineering, data engineering, or related roles with at least 2 years of hands-on AI experience developing generative AI or agentic AI solutions.
- Strong proficiency in Python programming and practical experience with Amazon Bedrock, AgentCore, LangChain, LangGraph, Model Context Protocol, and Strands Agents SDK or equivalent frameworks.
- Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or related field, or equivalent relevant experience.
- Experience required specifically includes designing and implementing AI agent workflows, multi-agent systems, prompt engineering, LLM orchestration, and production deployment in cloud environments.
Ideal Candidate Profile
- Experienced AI engineer with demonstrated ability to build and optimize multi-agent AI applications using modern agentic AI toolkits and cloud-native AWS environments.
- Comfortable working in cross-functional teams translating complex business requirements into scalable AI solutions that ensure measurable improvements in automation, reliability, and operational metrics.
- Strong background in designing secure, maintainable AI agent architectures, with practical knowledge of responsible AI practices, production-grade deployment, and performance evaluation.