Job Title: Senior Software Developer Full Stack & AI

Technologies: Node.js, React.js, React Native, MS SQL Server, Azure, Generative AI

Location: Bengaluru

Experience: 5 to 10 Years

Employment Type: Full-Time, Permanent

Work Mode: On-site

About the Role

We are hiring a Senior Software Developer Full Stack & AI who will play a critical role in designing, building, scaling, and maintaining enterprise-grade web, mobile, and AI-enabled applications.

The candidate will be responsible for end-to-end application development, from understanding business requirements and designing solutions to development, deployment, production support, and performance optimization.

In addition to strong Full Stack development expertise, the candidate should have practical knowledge of Generative AI, Large Language Models (LLMs), AI APIs, RAG, AI Agents, and AI-assisted application development.

The role requires strong expertise in Node.js, React.js, React Native, Microsoft SQL Server, Azure, cloud deployment, DevOps, and modern AI technologies.

The candidate should also be capable of mentoring junior developers and contributing to technical and architectural decisions.

Key Responsibilities

1. End-to-End Application Development

- Understand business requirements and convert them into scalable technical solutions.
- Develop backend services and APIs using Node.js.
- Build dynamic and responsive web applications using React.js.
- Develop cross-platform mobile applications using React Native.
- Design and integrate AI-enabled features into existing and current applications.
- Ensure clean, maintainable, secure, and reusable code.
- Take ownership of applications from requirement analysis to production deployment.

2. AI & Generative AI Development

- Develop AI-powered features using OpenAI, Azure OpenAI, or similar LLM platforms.
- Integrate Large Language Models into web, mobile, and enterprise applications.

- Build applications using

- Generative AI

- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)

- AI Agents

- Function/Tool Calling

- Embeddings

- Vector Search

- Natural Language Processing
- Develop AI-powered solutions such as:

- Intelligent chatbots

- AI assistants

- Document analysis systems

- Automated data extraction

- Document summarization

- Intelligent search

- Customer support assistants

- Business workflow automation
- AI-based reporting and insights
- Knowledge-base assistants
- Design effective prompts and structured outputs for LLM-based applications.
- Integrate AI models with internal databases, APIs, applications, and enterprise systems.
- Implement guardrails, validation, error handling, and monitoring for AI-generated responses.
- Optimize AI API usage for performance, accuracy, reliability, and cost.

3. AI Agent & Automation Development

- Build AI Agents capable of performing business tasks using APIs, databases, and external services.
- Develop agent-based workflows for business process automation.

- Integrate AI Agents with

- REST APIs

- SQL databases

- CRM systems

- Business applications

- Document repositories

- Microsoft services
- Third-party applications
- Implement tool/function calling for AI Agents.
- Develop multi-step AI workflows with proper validation and human approval where required.
- Evaluate AI responses for accuracy, reliability, and business relevance.

4. System Design & Architecture

- Design application architecture for scalability, reliability, security, and performance.
- Design architecture for traditional applications as well as AI-powered applications.
- Implement modular and microservices-based architecture where applicable.
- Define API contracts and ensure proper versioning and documentation.
- Design integration between applications, AI services, databases, and third-party APIs.
- Identify system bottlenecks and optimize application performance.
- Participate in technical architecture and technology selection decisions.

5. Backend & API Development

- Design and develop scalable RESTful APIs and microservices using Node.js.
- Integrate applications with external and internal APIs.
- Implement authentication and authorization using:

- JWT

- OAuth
- Role-Based Access Control
- Handle asynchronous processing, queues, and background jobs.
- Implement secure coding practices and proper data protection.
- Integrate AI APIs with backend services.
- Develop middleware and integration layers for AI-powered applications.

6. Database Design & Optimization

- Design normalized and scalable database structures using Microsoft SQL Server.

- Develop

- Stored Procedures

- Functions

- Triggers

- Views

- Optimized SQL Queries
- Perform query tuning and performance optimization.
- Implement indexing strategies.
- Handle transactional data and ensure data integrity.




- Design database structures to support AI application requirements.
- Integrate structured enterprise data with AI applications.

7. RAG & Enterprise Knowledge Solutions

- Build Retrieval-Augmented Generation (RAG) solutions using enterprise documents and databases.

- Process documents such as

- PDF

- Word

- Excel

- Emails
- Knowledge-base documents

- Business policies and manuals
- Generate and manage embeddings.
- Implement semantic search and vector search.
- Work with vector databases or vector search platforms.
- Build secure enterprise knowledge assistants.
- Ensure AI responses are grounded in approved business data.

8. Cloud Infrastructure & Deployment Deploy and manage applications on Microsoft Azure.

Experience with Azure services such as:

- Azure App Services
- Azure Virtual Machines
- Azure SQL
- Azure Storage Accounts
- Azure Functions
- Azure Key Vault
- Azure Monitor
- Azure Application Insights

Exposure to AI-related Azure services such as:
- Azure OpenAI
- Azure AI Services
- Azure AI Search

Manage environments including:
- Development
- QA / Testing
- UAT
- Pre-Production
- Production

Ensure high availability, scalability, security, backup, and disaster recovery readiness. 9. CI/CD & DevOps

- Design and maintain CI/CD pipelines using:

- Azure DevOps

- GitHub Actions

- Jenkins
- Automate application build, testing, and deployment workflows.
- Implement Git-based development workflows.
- Implement versioning and release management.
- Define rollback strategies.
- Manage environment-specific configurations and secrets securely.
- Monitor deployments and resolve deployment-related issues.

1. Production Support & Monitoring

- Handle production issues and application troubleshooting.
- Perform root-cause analysis.

- Monitor

- System performance

- Application logs

- API performance

- Errors

- Alerts

- AI API usage
- Monitor AI applications for inaccurate, incomplete, or unexpected responses.
- Ensure application uptime, reliability, and SLA adherence.
- Identify recurring problems and implement permanent solutions.

11. Code Quality & Best Practices

- Conduct code reviews.
- Enforce coding standards and development best practices.

- Implement

- Unit Testing

- Integration Testing

- API Testing

- Code Coverage
- Follow secure coding and compliance practices.
- Maintain technical documentation.
- Ensure reusable and modular application design.
- Use AI coding tools responsibly to improve developer productivity without compromising code quality.

12. Team Collaboration & Mentorship

- Work closely with Product Managers, Business Teams, QA, UI/UX, and Infrastructure teams.
- Mentor junior developers and guide them technically.

- Participate in

- Sprint Planning

- Estimation
- Daily Stand-ups

- Code Reviews

- Retrospectives
- Provide technical guidance on Full Stack and AI development.
- Evaluate current technologies and recommend appropriate solutions.

Technical Skills Must Have

Core Full Stack Technologies

Strong hands-on experience in:

- Node.js
- React.js
- React Native
- JavaScript / ES6+
- Microsoft SQL Server
- RESTful APIs

Programming & Development Concepts

Strong understanding of:

- JavaScript
- Asynchronous Programming
- Promises
- Async/Await
- REST APIs
- API Security
- Authentication
- Authorization
- JWT
- OAuth
- Data Structures
- Algorithms
- Object-Oriented and modular programming concepts

AI / Generative AI Skills The candidate should have practical exposure to Generative AI application development. Knowledge or hands-on experience in:

- Generative AI
- Large Language Models LLMs
- OpenAI APIs
- Azure OpenAI
- Prompt Engineering
- RAG Retrieval-Augmented Generation
- AI Agents
- Function / Tool Calling
- Embeddings
- Vector Search
- Semantic Search
- AI API Integration

Candidate should understand how to integrate LLMs into existing enterprise applications.

Database Skills

Hands-on experience with Microsoft SQL Server.

Robust knowledge of:

- Database Design
- Query Optimization
- Indexing
- Stored Procedures
- Functions
- Views
- Transactions
- Database Performance Optimization

Cloud & DevOps Experience with Microsoft Azure is preferred.

Knowledge of

- Microsoft Azure
- Azure App Services
- Azure SQL
- Azure Storage
- Azure OpenAI
- CI/CD Pipelines
- Azure DevOps
- GitHub Actions
- Git-based Workflows
- Deployment Automation

AI Development Tools Good to Have Experience with one or more of the following is an advantage:

- LangChain
- LangGraph




- Semantic Kernel
- LlamaIndex
- Azure AI Search
- Vector Databases
- Pinecone
- Chroma
- FAISS
- Qdrant
- Hugging Face
- Python for AI integrations

Deep Data Science or Machine Learning research experience is not mandatory. The focus is on building practical AI-powered enterprise applications using existing AI models and APIs. Other Good-to-Have Skills

- Microservices Architecture
- Docker
- Kubernetes
- Redis
- Caching Mechanisms
- RabbitMQ
- Kafka
- WebSockets
- Logging & Monitoring Tools
- Application Security
- BFSI Domain Experience
- CRM Application Development
- SaaS Product Development
- Workflow Automation
- Microsoft Power Automate
- Microsoft Graph API

AI-Assisted Software Development Candidate should be comfortable using modern AI development tools such as:
- GitHub Copilot
- ChatGPT
- Claude
- Cursor
- Codex or similar AI coding assistants

The candidate should understand how to use AI tools for:
- Code generation
- Code reviews
- Debugging
- Test-case generation
- Documentation
- API development
- Refactoring
- Development productivity

The candidate must still be capable of independently understanding, validating, debugging, and maintaining AI-generated code.

Soft Skills

- Robust problem-solving ability.
- Excellent communication skills.
- Strong analytical and debugging skills.
- Ability to work independently.
- Ownership mindset.
- Ability to understand business problems and translate them into technical solutions.
- Ability to mentor and guide junior developers.
- Willingness to continuously learn emerging technologies, particularly AI.

Key Performance Indicators – KPIs Performance will be measured based on:

- Timely delivery of features and releases.
- Code quality and maintainability.
- Application performance and uptime.
- Reduction in production issues.
- Quality of technical architecture.
- Successful implementation of AI-enabled features.
- Development productivity improvements through automation and AI.
- Contribution to architecture and technology improvements.
- Ability to mentor and support junior developers.
- Quality of production support and issue resolution.

What We Expect We are looking for someone with:

- Strong ownership mindset – not just task execution.
- Ability to independently handle applications from development to production.
- Ability to solve real-world production challenges.
- Strong Full Stack development fundamentals.
- Interest and practical understanding of Generative AI.
- Ability to quickly learn and implement emerging AI technologies.
- Strong commitment to quality and deadlines.
- Continuous learning and adaptability.

We are not looking only for someone who knows how to use ChatGPT. The candidate should understand how to integrate AI into software applications and business processes.

Why Join Us

- Opportunity to work on real business-critical applications across BFSI, CRM, SaaS, and enterprise automation.
- Work on both traditional applications and modern AI-powered applications.
- Exposure to complete end-to-end product development.
- Opportunity to build Generative AI, RAG, and AI Agent-based solutions.
- Work with modern cloud, mobile, web, and AI technologies.
- Opportunity to participate in architectural and technology decisions.

- Career growth opportunities towards

- Technical Lead

- AI Application Lead

- Solution Architect

- Technical Architect

Role Details Role: Senior Full Stack Developer – Full Stack & AI

Industry Type: IT Services & Consulting

Department: Engineering – Software & QA

Employment Type: Full Time, Permanent

Role Category: Software Development

Education

UG: Any Graduate

Computer Science / Information Technology / Engineering background preferred but not mandatory for candidates with strong relevant experience.

Key Skills

Preferred Key Skills:

Node.js, React.js, React Native, JavaScript, Microsoft SQL Server, Full Stack Development, Generative AI, OpenAI API, Azure OpenAI, Large Language Models, LLM, RAG, AI Agents, Prompt Engineering, Function Calling, Embeddings, Vector Search, RESTful APIs, JWT, OAuth, Authentication, Authorization, Microsoft Azure, Azure DevOps, CI/CD Pipeline, GitHub Actions, Microservices, Application Security, Docker, Redis, Message Queue, GitHub, Agile Development, BFSI, CRM, SaaS.

Candidate Screening Preference

Preference will be given to candidates who can demonstrate at least one working AI application or project, such as:

- AI chatbot connected to company data
- RAG-based document assistant
- AI Agent integrated with APIs or databases
- Document extraction or summarization application
- AI-based customer service application
- AI-powered business workflow
- LLM integration within an existing Node.js / React application

Candidates should be prepared to explain what they personally developed, the architecture used, the AI model/API used, and how the solution was deployed.

📌 Senior Software Developer - Full Stack & AI (Bengaluru)
🏢 TANTRANOVA TECHNOLOGY
📍 Bengaluru