AI Full Stack Engineer - React - Python_AWS_Langchain

Job Description: Full Stack AI Engineer (Python & React)

Role Title: Full Stack AI Engineer

Band / Level: 5 10 years

Location: Gurugram

Employment Type: Full-time

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: 5-10years 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.

Preferred / Nice-to-Have

• Experience setting up automated CI/CD pipelines via GitHub Actions.
• Familiarity with AgentCore frameworks or custom autonomous agent design patterns.
• Experience handling asynchronous event-driven architectures (e.g., SQS, Kafka, Celery).

Competencies & Attributes

• Strong analytical and problem-solving abilities.
• Focus on clean code, documentation, and automated testing.
• Collaborative mindset with strong communication skills across cross-functional engineering teams.