Agentic AI Engineer – AWS Bedrock, LangGraph, RAG & Multi-Agent Systems
Synechron (company site, opens in a new tab)3+ yrsPuneOn-siteDirect career pageEst. 15–28 LPA
Posted 2d ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and scale autonomous, production-grade multi-agent AI systems using AWS Bedrock.
- Develop and maintain advanced Retrieval-Augmented Generation (RAG) pipelines and semantic search infrastructure with vector databases.
- Implement robust AI workflows including reasoning, planning, memory, tool-calling, and safe human-in-the-loop automation to drive intelligent workflow automation and operational efficiency.
Minimum Requirements
- 3-5+ years of core software development experience with at least 1-2 years focused on production-level LLM and agentic AI workflows.
- Expert-level proficiency in Python and asynchronous backend API frameworks (e.g., FastAPI, Flask).
- Hands-on experience with AWS Bedrock platform, AWS services (EC2, Lambda, IAM, VPCs, Step Functions), multi-agent orchestration frameworks (e.g., LangGraph), and vector databases (e.g., Pinecone, OpenSearch).
- Bachelor's or Master's degree in Computer Science, IT, Engineering, AI, or related field; equivalent practical experience may be considered.
Ideal Candidate Profile
- Experienced in architecting and deploying scalable multi-agent systems with solid expertise in RAG and vector search pipelines for enterprise AI applications.
- Demonstrates strong capability in translating complex business processes into deterministic, code-driven autonomous AI workflows maintaining operational, security, and compliance standards.
- Skilled in cross-functional collaboration with teams across product, security, and operations to deliver secure, cost-effective, and maintainable AI solutions in regulated or data-sensitive environments.