TANTRANOVA TECHNOLOGY PVT LTD
Senior Software Developer - Full Stack & AI
Skills
2 months ago
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Important information
Contract type:
Permanent
Location:
Bengaluru, Karnataka, India
Work mode:
Onsite
Published on:
10 August 2026
What they need
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 new 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.
- 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 new 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.
Strong 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
- Strong 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.
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