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AI Engineer (NCS/Job/ 3735)

For A Leading Co Provider Of Digital And Ai Solutions And Products
3 - 7 Years
Full Time
Immediate
Up to 19 LPA
1 Position(s)
Remote - Wfh
Posted 3 Days Ago

Job Skills

Job Description

Role Overview

We are seeking a skilled AI Application Developer to support ongoing AI initiatives. The ideal candidate will have hands-on experience building AI-powered applications using modern LLMs (specifically Anthropic Claude) and full-stack development expertise across web technologies.

Key Responsibilities

  • Design and develop AI-driven applications leveraging Claude (Anthropic) models
  • Build and integrate backend services using Python-based frameworks (e.g., FastAPI, Flask)
  • Develop responsive and scalable front-end applications using React.js
  • Design and manage relational databases (preferably PostgreSQL)
  • Implement end-to-end full-stack solutions, including APIs, UI, and data layers
  • Integrate LLM capabilities into enterprise applications (RAG, prompt orchestration, workflows)
  • Collaborate with cross-functional teams including product owners, infrastructure and DevOps
  • Ensure code quality, security, scalability, and performance best practices

Required Skills

  • 3–7 years of experience in full-stack development
  • Strong experience with Claude (Anthropic) or similar LLM-based application development
  • Proficiency in Python and modern backend frameworks (FastAPI/Flask/Django)
  • Solid experience with React.js and modern JavaScript/TypeScript
  • Hands-on experience with PostgreSQL or comparable relational databases
  • Experience with REST APIs, microservices architecture, and integration patterns
  • Experience with prompt engineering, RAG, and AI application design patterns, multi-agent orchestration,
  • Experience with Agent Frameworks, Claude Tool/plugin (function calling) integration, hooks/lifecycle management, reusable skills design
  • Experience with version control systems (Git) and CI/CD pipelines

Preferred Qualifications

  • Experience with cloud platforms (AWS, Azure, or GCP)
  • Experience with vector databases (e.g., Azure AI Search, Pinecone, FAISS etc.)
  • Understanding of enterprise system integrations
  • Exposure to containerization (Docker, Kubernetes)
  • Knowledge of security and compliance requirements for AI applications