Role Overview

We are looking for experienced Full Stack Engineers with strong hands-on expertise in AWS cloud technologies and the ability to design, develop, and deliver Agentic AI use cases. The ideal candidate should have experience building scalable full-stack applications, integrating Generative AI solutions, and leveraging AWS services such as Amazon Bedrock, Kiro, and Amazon QuickSight to develop intelligent, business-driven applications.

Key Responsibilities

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Design, develop, and maintain scalable full-stack applications using modern frontend and backend technologies.

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Build and implement Agentic AI solutions capable of executing multi-step tasks, reasoning, and workflow automation.

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Develop AI agents and Generative AI applications using Amazon Bedrock, including foundation models, tool calling, and agent orchestration.

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Leverage Kiro for AI-assisted software development and application delivery.

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Integrate AI-powered capabilities into existing enterprise applications, APIs, and business workflows.

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Develop interactive dashboards, reports, and business intelligence solutions using Amazon QuickSight.

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Design and implement secure, scalable cloud-native applications using AWS services.

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Build and integrate REST APIs, microservices, databases, and third-party systems.

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Implement authentication, authorization, logging, monitoring, and security best practices.

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Collaborate with product owners, architects, and cross-functional teams to translate business requirements into technical solutions.

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Optimize application performance, reliability, scalability, and cloud costs.

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Follow CI/CD, version control, testing, and deployment best practices.

Required Skills

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Full Stack Development:



5+ years of experience in application development using frontend and backend technologies.

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AWS Cloud: Hands-on experience with AWS services, architecture, deployment, and application integration.

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Agentic AI: Experience developing AI agents, autonomous workflows, tool calling, multi-step orchestration, and enterprise AI use cases.

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Amazon Bedrock: Experience with foundation models, prompt engineering, knowledge bases, RAG, and agent-based applications.

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Kiro: Familiarity with AI-powered development workflows using Kiro.

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Amazon QuickSight: Experience creating dashboards, visualizations, reports, and business insights.

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Backend Development: Experience with Python, Node.js, Java, or similar backend technologies.

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Frontend Development: Experience with React, Angular, or similar modern frontend frameworks.

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API & Integration: Strong knowledge of REST APIs, microservices, and system integration.

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Database: Experience with SQL/NoSQL databases and data modeling.

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DevOps: Familiarity with Git, CI/CD pipelines, automated testing, and cloud deployment.

AWS Certification

Candidates should hold a relevant AWS certification, preferably one of the following:

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AWS Certified Developer – Associate

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AWS Certified Solutions Architect – Associate

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AWS Certified Machine Learning Engineer – Associate

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AWS Certified AI Practitioner

Preferred Qualifications

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Experience delivering production-grade Generative AI or Agentic AI applications.

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Knowledge of RAG architectures, vector databases, embeddings, and prompt optimization.

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Experience with AWS Lambda, API Gateway, Amazon S3, IAM, CloudWatch, and other AWS services.

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Understanding of AI security, responsible AI practices, monitoring, and evaluation.

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Robust problem-solving, communication, and collaboration skills.

📌 Full Stack Engineer Agentic AI (AWS) (India)
🏢 Important Business
📍 India