Full Stack Developer (AI-Enabled Applications)

Vrinda International; Bengaluru; On-site; INR 2,800,000 - 4,200,000; Full time

Job summary

Vrinda International in Bengaluru, India is seeking a seasoned Full Stack Developer specializing in AI to design, build, and maintain robust AI-driven applications. You will leverage ML models and cloud-native architectures to deliver scalable solutions that integrate with enterprise systems.

The role requires bridging traditional web development with generative AI, ensuring secure, efficient apps aligned with responsible AI, and leading front-end and back-end orchestration for AI features.

Qualifications

• 6–9 years of software development experience in IT services.
• Hands-on with Generative AI, LLMs, Prompt Engineering, and AI Orchestration frameworks.
• Cloud & DevOps experience with AWS or Azure; Terraform (HCL) and Shell scripting.

Responsibilities

• Implement AI capabilities by integrating LLMs and Generative AI tools into core workflows.
• Design and manage Retrieval-Augmented Generation (RAG) pipelines for enhanced data retrieval.
• Engineer secure cloud infrastructure using AWS or Azure with microservices patterns.
• Automate deployment and configuration with Terraform (HCL) and shell scripts.
• Develop and maintain RESTful APIs and microservices for AI components and client apps.
• Embed security and privacy controls in the AI development lifecycle for responsible AI.
• Use Python to build automation scripts, integrate AI models and manage API interactions.

Skills

AI/ML concepts

Generative AI

LLMs

Prompt engineering

REST APIs

Microservices

Python scripting

Terraform (HCL)

Shell scripting

AWS/Azure clouds

Tools

AWS

Azure

REST framework

Job description

Full Stack Developer (AI-Enabled Applications)

Job Description

Full Stack Developer (AI-Enabled Applications)

Summary

We are seeking a seasoned Full Stack Developer with specialized expertise in artificial intelligence to design, build, and maintain robust AI-driven applications. In this pivotal role, you will leverage advanced machine learning models and cloud-native architectures to deliver scalable solutions that integrate seamlessly with existing enterprise systems. The ideal candidate will bridge the gap between traditional web development and cutting-edge generative AI technologies, ensuring that all applications are secure, efficient, and aligned with responsible AI principles. This position is critical for driving innovation in our IT services sector, requiring a deep understanding of both front-end user experiences and back-end AI orchestration.

Responsibilities

• Implement advanced AI capabilities by integrating Large Language Models (LLMs) and Generative AI tools into core business workflows.
• Design and manage Retrieval-Augmented Generation (RAG) pipelines to enhance application intelligence and data retrieval accuracy.
• Engineer secure cloud infrastructure using AWS or Azure, focusing on cloud-native patterns and microservices architecture.
• Automate deployment and configuration processes through Terraform (HCL) and Shell scripting to ensure reliable and repeatable environments.
• Develop and maintain RESTful APIs and microservices to facilitate seamless communication between AI components and client applications.
• Embed security and data privacy protocols directly into the AI development lifecycle to uphold responsible AI standards.
• Utilize Python to build automation scripts, integrate AI models, and manage API interactions for enhanced system performance.

Requirements

Requirements:

• Experience: A proven track record of 6 to 9 years in software development, specifically within the IT Services industry.
• AI & Machine Learning: Hands-on experience with Generative AI, LLMs, Prompt Engineering, and AI Orchestration frameworks.
• Cloud & DevOps: Strong background in AWS or Azure cloud platforms, including expertise in Terraform (HCL) and Shell scripting for infrastructure as code.
• Architecture: Demonstrated ability to design and implement microservices, REST APIs, and cloud-native architectures.
• Security & Compliance: Knowledge of Responsible AI practices, data privacy regulations, and security best practices for AI applications.