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AI Engineer – Agentic AI | Offshore

Photon
Location
India
Workplace
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Employment
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Posted 8d ago

  • 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.

Skills

  • Python
  • LangChain
  • LangGraph
  • Bedrock
  • Retrieval-Augmented Generation
  • Embeddings
  • Vector Databases
  • AWS
  • Generative AI
  • LLM
  • Prompt Engineering
  • Git
  • AWS Lambda
  • S3
  • API Gateway
  • DynamoDB
  • IAM
  • AWS CloudWatch
  • Docker
  • Model Context Protocol

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