Software Engineering Mts (node.js, React.js, Aws- Full Stack) + AI

Salesforce Salesforce · Enterprise · Bangalore, India

Full Stack Software Engineer with a focus on integrating AI/ML capabilities, including LLM-based agents and AI workflows, into production systems. Requires experience with Node.js, React.js, AWS, and familiarity with AI agents, LLMs, prompt engineering, RAG, and vector databases.

What you'd actually do

  1. Design, develop, and maintain full-stack applications using modern frameworks and best practices
  2. Build and optimize microservices architectures for scalability and performance
  3. Integrate AI/ML capabilities into production systems, including LLM-based agents and AI workflows
  4. Develop RESTful APIs and backend services using Java, Python, and Node.js
  5. Create responsive, performant frontend applications using React.js

Skills

Required

  • Node.js
  • React.js
  • AWS
  • Java
  • Python
  • Microservices
  • Databases (relational and NoSQL)
  • AI/ML fundamentals
  • AI agents
  • LLMs
  • Git
  • CI/CD
  • Docker
  • Kubernetes

Nice to have

  • Prompt engineering
  • AI agent orchestration
  • Vector databases
  • RAG
  • Serverless architectures
  • Cloud-native development
  • Infrastructure as code
  • System design
  • Distributed systems
  • Monitoring
  • Observability
  • Production debugging

What the JD emphasized

  • Solid experience with Node.js backend development
  • Strong proficiency in React.js for frontend development
  • 2–5 years of professional software development experience
  • Working knowledge of cloud platforms (AWS, Azure, or GCP)
  • Proficiency in Java and/or Python for backend services
  • Hands-on experience building and deploying microservices architectures
  • Strong understanding of relational and NoSQL databases (design, optimization, and querying)
  • Understanding of AI/ML fundamentals and practical experience integrating AI into applications
  • Familiarity with AI agents, LLMs (Claude, Gemini, GPT), and MCP (Model Context Protocol) servers
  • Experience with modern development practices: Git, CI/CD, testing, and containerization (Docker/Kubernetes)
  • Experience with prompt engineering and AI agent orchestration
  • Knowledge of vector databases and RAG (Retrieval-Augmented Generation) architectures

Other signals

  • Integrate AI/ML capabilities into production systems, including LLM-based agents and AI workflows
  • Familiarity with AI agents, LLMs (Claude, Gemini, GPT), and MCP (Model Context Protocol) servers
  • Experience with prompt engineering and AI agent orchestration
  • Knowledge of vector databases and RAG (Retrieval-Augmented Generation) architectures