AI Engineer – Agentic AI at Fa Ertb Saasfaprod1 — India

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About The Role

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 .
Strong 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 .
Strong 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 .
Strong 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 .
Strong 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.