Senior Software Developer Full Stack & AI

Senior Software Developer Full Stack & AI

Location: Bengaluru
Experience: 5 - 10 Years
Employment Type: Full-Time, Permanent
Work Mode: On-site

Primary Technologies

Node.js | React.js | React Native | MS SQL Server | Microsoft Azure | Generative AI | LLM | RAG | AI Agents

About the Role

We are looking for an experienced Senior Software Developer Full Stack & AI who can independently design, develop, deploy, and support enterprise-grade web, mobile, and AI-enabled applications.

The candidate should have strong hands-on experience in Node.js, React.js, React Native, Microsoft SQL Server, REST APIs, and Microsoft Azure, along with practical exposure to modern Generative AI technologies such as LLMs, RAG, AI Agents, OpenAI/Azure OpenAI APIs, embeddings, and vector search.

This is an end-to-end development role requiring strong technical ownership — from understanding business requirements and designing solutions to development, deployment, production support, performance optimization, and mentoring junior developers.

Key Responsibilities

Full Stack Application Development

• Understand business requirements and convert them into scalable technical solutions.
• Develop scalable backend services and REST APIs using Node.js.
• Build responsive web applications using React.js.
• Develop cross-platform mobile applications using React Native.
• Design clean, secure, reusable, and maintainable application components.
• Take ownership of applications from requirement analysis through production deployment and support.

Generative AI & AI Application Development

• Build AI-powered applications using OpenAI, Azure OpenAI, or similar LLM platforms.
• Integrate LLM capabilities into existing web, mobile, and enterprise applications.
• Develop solutions using:
• Generative AI
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• AI Agents
• Function / Tool Calling
• Vector Search
• Semantic Search
• Natural Language Processing

• Build practical AI solutions such as:
• AI Chatbots and Assistants
• Enterprise Knowledge Assistants
• Document Analysis & Summarization
• Automated Data Extraction
• Intelligent Search
• Customer Support Assistants
• AI-based Reporting & Insights
• Business Workflow Automation
• Integrate AI models with internal databases, REST APIs, applications, and enterprise systems.
• Implement structured outputs, validation, guardrails, error handling, and monitoring.
• Optimize AI API usage for accuracy, performance, reliability, and cost.

AI Agents & Automation

• Build AI Agents capable of performing business tasks using APIs, databases, and external systems.
• Develop multi-step AI-driven workflows.
• Implement tool/function calling for AI Agents.
• Integrate agents with:
• REST APIs
• SQL Databases
• CRM Systems
• Business Applications
• Document Repositories
• Microsoft Services
• Third-party Applications
• Implement validation and human approval workflows where required.
• Evaluate AI-generated responses for accuracy and business relevance.

System Design & Architecture

• Design scalable, secure, reliable, and high-performance application architectures.
• Design architecture for traditional as well as AI-powered applications.
• Implement modular or microservices-based architecture where appropriate.
• Define API standards, versioning, and documentation.
• Design integration between applications, databases, AI services, and third-party APIs.
• Identify performance bottlenecks and implement improvements.
• Contribute to architecture and technology selection decisions.

Backend & API Development

• Design and develop scalable RESTful APIs and microservices using Node.js.
• Integrate internal and third-party APIs.
• Implement secure authentication and authorization using:
• JWT
• OAuth
• Role-Based Access Control
• Handle asynchronous processing, queues, and background jobs.
• Apply secure coding and data-protection practices.
• Develop middleware and integration layers for AI-enabled applications.

Database Development

Strong hands-on experience with Microsoft SQL Server, including:

• Database Design
• Stored Procedures
• Functions
• Views
• Triggers
• Transactions
• Complex SQL Queries
• Query Optimization
• Indexing
• Performance Tuning
• Data Integrity

The candidate should also understand how structured enterprise data can be integrated securely with AI applications.

RAG & Enterprise Knowledge Solutions

• Build RAG solutions using enterprise documents and databases.
• Process content from:
• PDF
• Word
• Excel
• Emails
• Business Policies
• Manuals
• Knowledge-base Documents
• Generate and manage embeddings.
• Implement semantic search and vector search.
• Work with vector databases/search platforms.
• Build secure enterprise knowledge assistants.
• Ensure AI responses are grounded in approved business data.

Microsoft Azure & Cloud

Experience with Microsoft Azure and cloud deployment is preferred.

Exposure to:

• Azure App Services
• Azure Virtual Machines
• Azure SQL
• Azure Storage
• Azure Functions
• Azure Key Vault
• Azure Monitor
• Application Insights
• Azure OpenAI
• Azure AI Services
• Azure AI Search

Candidate should understand deployment and management across:

Development QA/Testing UAT Pre-Production Production

Knowledge of application scalability, availability, backup, security, and disaster recovery is expected.

DevOps & CI/CD

Experience with:

• Azure DevOps
• GitHub Actions
• Jenkins
• Git
• CI/CD Pipelines
• Automated Build & Deployment
• Release Management
• Environment Configuration
• Secret Management
• Rollback Strategies

Production Support & Monitoring

• Troubleshoot production issues and perform root-cause analysis.
• Monitor application logs, APIs, errors, alerts, and system performance.
• Monitor AI applications for inaccurate or unexpected responses.
• Improve application uptime, reliability, and performance.
• Identify recurring issues and implement permanent solutions.

Code Quality & Engineering Practices

• Conduct code reviews.
• Follow and enforce coding standards.
• Implement:
• Unit Testing
• Integration Testing
• API Testing
• Code Coverage
• Follow secure coding practices.
• Maintain technical documentation.
• Build reusable and modular components.
• Use AI coding tools responsibly while independently validating AI-generated code.

Team Collaboration & Mentoring

• Work closely with Product, Business, QA, UI/UX, and Infrastructure teams.
• Mentor and technically guide junior developers.
• Participate in:
• Sprint Planning
• Estimation
• Daily Stand-ups
• Code Reviews
• Retrospectives
• Evaluate emerging technologies and recommend suitable solutions.

Mandatory Technical Skills

Strong hands-on experience in:

• Node.js
• React.js
• React Native
• JavaScript / ES6+
• Microsoft SQL Server
• RESTful APIs
• JWT / OAuth
• Authentication & Authorization
• API Security
• Async/Await & Promises
• Git-based Development

Generative AI Skills

Practical exposure to:

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

The candidate should understand how to integrate LLMs into real enterprise applications, rather than simply using AI tools.

Good-to-Have AI Technologies

Experience with one or more of the following would be an advantage:

• LangChain
• LangGraph
• Semantic Kernel
• LlamaIndex
• Azure AI Search
• 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 enterprise applications using existing AI models and APIs.

Additional Good-to-Have Skills

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

AI-Assisted Development

Candidate should be comfortable using modern development tools such as:

• GitHub Copilot
• ChatGPT
• Claude
• Cursor
• Codex or similar AI coding assistants

AI tools may be used for code generation, debugging, testing, documentation, code reviews, API development, and refactoring.

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

Soft Skills

• Strong problem-solving and analytical ability.
• Strong debugging skills.
• Good communication skills.
• Ability to work independently.
• Strong ownership mindset.
• Ability to understand business problems and translate them into technical solutions.
• Ability to mentor junior developers.
• Willingness to continuously learn emerging technologies.

What We Expect

We are looking for someone who:

• Takes ownership rather than simply completing assigned tasks.
• Can independently handle applications from development through production.
• Can solve real-world production and performance issues.
• Has strong Full Stack development fundamentals.
• Understands practical Generative AI application development.
• Can quickly learn and implement emerging technologies.
• Maintains high standards for quality and delivery timelines.

We are not looking only for someone who knows how to use ChatGPT or AI coding tools.

The candidate should understand how AI can be integrated into software applications, enterprise data, APIs, and business processes.

Candidate Screening Preference

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

• AI Chatbot connected to enterprise/company data
• RAG-based Document Assistant
• AI Agent integrated with APIs or databases
• Document Extraction or Summarization Application
• AI-powered Customer Service Solution
• AI-enabled Business Workflow
• LLM integration within an existing Node.js / React application

Candidates should be prepared to explain:

• What they personally developed
• Application architecture
• AI model/API used
• Integration approach
• Deployment architecture
• Challenges faced and solutions implemented

Education

UG: Any Graduate

Computer Science, Information Technology, or Engineering background preferred, but not mandatory for candidates with strong relevant hands-on experience.

Key Skills

Node.js | React.js | React Native | JavaScript | Microsoft SQL Server | Full Stack Development | Generative AI | OpenAI API | Azure OpenAI | LLM | RAG | AI Agents | Prompt Engineering | Function Calling | Embeddings | Vector Search | REST APIs | JWT | OAuth | Microsoft Azure | Azure DevOps | CI/CD | GitHub Actions | Microservices | Application Security | Docker | Git | BFSI | CRM | SaaS

Career Opportunity

The role provides exposure to business-critical applications across BFSI, CRM, SaaS, enterprise automation, web, mobile, cloud, and Generative AI, with potential career progression towards:

• Technical Lead
• AI Application Lead
• Solution Architect
• Technical Architect