Responsibilities
Design and develop AI agents, super-agent/sub-agent architectures, and agentic workflows using Python, LangChain, and LangGraph.
Build production-ready AI solutions using Amazon Bedrock.
Design and implement super-agent and sub-agent patterns for complex, multi-step business workflows.
Develop agents capable of tool calling, API invocation, information retrieval, and multi-step task execution.
Design prompts, tool definitions, structured outputs, agent state, and workflow orchestration.
Integrate AI agents with REST APIs, databases, enterprise applications, and external services.
Build RAG-based solutions using embeddings, vector databases/search, and enterprise knowledge sources.
Implement reliability mechanisms including error handling, retries, validation, fallback strategies, and guardrails.
Test, evaluate, and improve agent responses for accuracy, reliability, and consistency.
Develop clean, scalable, and maintainable Python services and APIs.
Work with senior engineers and architects to integrate and deploy AI solutions into AWS cloud environments.
Required Skills
Approximately 5 years of software development experience.
Solid Python programming skills.
Hands-on experience building Generative AI / LLM applications.




Practical experience building and implementing AI agents or agentic workflows.
Mandatory hands-on experience with Amazon Bedrock.
Solid understanding of super-agent and sub-agent concepts, architectures, and orchestration.
Experience with LangChain and/or LangGraph.
Experience integrating LLMs through APIs.
Hands-on experience with RAG, embeddings, vector databases, and vector search.
Solid understanding of:
Prompt engineering
Function/tool calling
Structured LLM outputs
Agent state and workflow orchestration
Super-agent/sub-agent patterns
RAG fundamentals
Embeddings and vector search
LLM response validation and error handling
Experience building and consuming REST APIs.
Solid understanding of software engineering fundamentals, Git, testing, debugging, and code quality.
Preferred Skills
Experience with Amazon Bedrock AgentCore.
Experience with AWS services such as:
AWS Lambda
Amazon S3
API Gateway
DynamoDB
IAM
CloudWatch
Experience deploying AI applications using Docker and AWS cloud services.
Exposure to MCP (Model Context Protocol) or similar AI tool-integration protocols.
Experience with LLM evaluation, observability, tracing, or agent performance monitoring.

📌 Ai Engineer – Agentic Ai Offshore Tamil Nadu (India)
🏢 Photon
📍 India