CRESCENDO GLOBAL LEADERSHIP HIRING INDIA PRIVATE L
AI Full Stack Engineer - Python/React.js
- Compensation
- Not disclosed
- Location
- Gurgaon/Gurugram
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Fullstack
- Posted
Skills
Full description
Job Description : Full Stack AI Engineer (Python & React)Role Overview :
We are looking for a hands-on Full Stack AI Engineer to design, build, and deploy production-grade, AI-powered applications. In this role, you will bridge modern web interfaces with scalable Python backends and agentic workflows, taking features from concept to production on AWS cloud infrastructure.
Key Responsibilities :
- Frontend Architecture : Develop responsive, type-safe user interfaces and conversational dashboards using React and TypeScript.
- Backend & API Development : Design and implement robust backend services, microservices, and REST/GraphQL APIs in Python, ensuring thorough test automation (unit, integration, and end-to-end).
- AI Orchestration & Agent Workflows : Build multi-agent architectures, LLM orchestration layers, and evaluation pipelines using LangChain, LangGraph, and MLflow.
- Cloud & Infrastructure as Code : Provision, deploy, and manage scalable cloud resources on AWS using AWS CDK and containerize applications with Docker.
- Data Management : Model relational schemas, write high-performance SQL queries, and manage data persistence using PostgreSQL; integrate analytics workflows with Databricks.
- Quality & Collaboration : Partner closely with data scientists, product managers, and cloud engineers to take prototypes to resilient, enterprise-ready deployments.
Required Qualifications & Experience :
- Experience : 5 - 10 years of relevant full-stack software development experience.
- Frontend : Strong proficiency in React, TypeScript, state management, and modern CSS/UI libraries.
- Backend : Advanced Python programming skills with a strong discipline around writing testable code (e.g., pytest, unittest, mocks).
- AI Stack : Practical experience building LLM-driven applications using LangChain and multi-agent coordination using LangGraph; experiment tracking and model registry workflows with MLflow.
- Databases : Solid understanding of relational database design, query optimization, and schema migrations with PostgreSQL.
- Cloud & DevOps : Hands-on experience writing Infrastructure as Code (IaC) via AWS CDK, along with containerization and image creation using Docker.
- Data Platforms : Practical exposure to data workflows and lakehouse environments in Databricks.