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

- Design, develop, and maintain scalable full-stack applications using up-to-date frontend and backend technologies.
- Build and implement Agentic AI solutions capable of executing multi-step tasks, reasoning, and workflow automation.
- Develop AI agents and Generative AI applications using Amazon Bedrock, including foundation models, tool calling, and agent orchestration.
- Leverage Kiro for AI-assisted software development and application delivery.
- Integrate AI-powered capabilities into existing enterprise applications, APIs, and business workflows.
- Develop interactive dashboards, reports, and business intelligence solutions using Amazon QuickSight.
- Design and implement secure, scalable cloud-native applications using AWS services.
- Build and integrate REST APIs, microservices, databases, and third-party systems.
- Implement authentication, authorization, logging, monitoring, and security best practices.
- Collaborate with product owners, architects, and cross-functional teams to translate business requirements into technical solutions.
- Optimize application performance, reliability, scalability, and cloud costs.
- Follow CI/CD, version control, testing, and deployment best practices.

Required Skills

- Full Stack Development:



5+ years of experience in application development using frontend and backend technologies.
- AWS Cloud: Hands-on experience with AWS services, architecture, deployment, and application integration.
- Agentic AI: Experience developing AI agents, autonomous workflows, tool calling, multi-step orchestration, and enterprise AI use cases.
- Amazon Bedrock: Experience with foundation models, prompt engineering, knowledge bases, RAG, and agent-based applications.
- Kiro: Familiarity with AI-powered development workflows using Kiro.
- Amazon QuickSight: Experience creating dashboards, visualizations, reports, and business insights.
- Backend Development: Experience with Python, Node.js, Java, or similar backend technologies.
- Frontend Development: Experience with React, Angular, or similar modern frontend frameworks.
- API &
- Integration: Strong knowledge of REST APIs, microservices, and system integration.
- Database: Experience with SQL/NoSQL databases and data modeling.
- 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:
- AWS Certified Developer –
- Associate
- AWS Certified Solutions Architect –
- Associate
- AWS Certified Machine Learning Engineer –
- Associate
- AWS Certified AI Practitioner

Preferred Qualifications

- Experience delivering production-grade Generative AI or Agentic AI applications.
- Knowledge of RAG architectures, vector databases, embeddings, and prompt optimization.
- Experience with AWS Lambda, API Gateway, Amazon S3, IAM, CloudWatch, and other AWS services.
- Understanding of AI security, responsible AI practices, monitoring, and evaluation.
- Strong problem-solving, communication, and collaboration skills.

Skills: kiro,bedrock,aws

📌 Full Stack Engineer – Agentic AI (AWS) (Mumbai)
🏢 Zorba AI
📍 Mumbai