AI Full stack Engineer (Gen AI+ React/Angular +Node)

Crescendo Global Leadership Hiring India; Gurugram District, Bengaluru; Hybrid; INR 2,400,000 - 4,000,000; Full time

Job summary

Crescendo Global Leadership Hiring India is seeking a Full Stack AI Engineer to drive architecture, development, and deployment for an AI-powered claims platform.

You will bridge ML pipelines, production MLOps, and robust backend services with interactive UIs, operationalizing NLP/LLM models and multilingual processes.

Qualifications

• 4–10 years of experience in full-stack AI/ML engineering.
• Strong focus on UI, backend services, and ML deployment.
• Experience with cloud and data pipelines is required.

Responsibilities

• Develop responsive web interfaces and robust API services.
• Deploy and monitor ML models in production with CI/CD pipelines.
• Integrate NLP modules and multilingual search capabilities.
• Design data pipelines and manage cloud infrastructure (AWS, Airflow).

Skills

React

Angular

JavaScript

TypeScript

HTML5/CSS3

Node.js

Express/NestJS

Python

REST APIs

GraphQL

WebSockets

Tools

MLflow

Databricks

Docker

AWS EKS

Apache Airflow

S3

Aurora PostgreSQL

Liquibase

Job description

Job Description: Full Stack AI Engineer Claims Intelligence & MLOps

Experience Level: 4- 10 Years

Location: Hybrid - Gurugram/ Bangalore

About the Role

We are seeking a Full Stack AI Engineer to drive end-to-end architecture, development, and deployment for our AI-powered Claims Intelligence platform. In this expanded role, you will bridge machine learning pipelines, production MLOps deployment, robust backend services, and interactive user interfaces. You will operationalize deep NLP/LLM models, design data workflows, and deliver complete, client-facing web applications.

Key Responsibilities

• Full Stack & Application Development:
  • Build responsive, scalable web interfaces using React or Angular.
  • Develop robust API services and microservices using Node.js, JavaScript / TypeScript, and Python (FastAPI / Flask).
  • Build intuitive workflows, dashboards, and review tools for underwriters, adjusters, and portfolio managers.
• MLOps & Production Model Deployment:
  • Package, version, deploy, and monitor machine learning models in production using MLflow and Databricks.
  • Build real-time and batch model inference endpoints deployed via containerized environments (Docker, Kubernetes / AWS EKS).
  • Implement automated CI/CD pipelines, model drift monitoring, and evaluation tracking.
• AI Module Integration & NLP:
  • Operationalize and connect NLP modules: entity extraction, document classification, de-identification (DEID), and PII masking.
  • Implement hybrid search pipelines using GTE multilingual embeddings and vector search (pgvector / Aurora PostgreSQL).
  • Integrate LLM APIs (OpenAI / open-source models) for multilingual summarization, query expansion, and trend detection.
• Data Pipelines & Cloud Infrastructure:
  • Author and maintain batch and streaming workflows using Apache Airflow DAGs.
  • Manage AWS cloud services including S3, Athena, Glue, Fargate, EKS, SQS, and Step Functions.
  • Design ingestion pipelines parsing nested JSON, PDF attachments, and multilingual unstructured document data.

Required Skills & Experience

Frontend

React, Angular, JavaScript (ES6+), TypeScript, HTML5/CSS3

Backend

Node.js, Express/NestJS, Python, REST APIs, GraphQL, WebSockets

MLOps & Deployment

MLflow, Databricks, Docker, AWS EKS, CI/CD pipelines, Model Monitoring

AI / NLP & Search

LLM APIs (OpenAI), RAG architectures, GTE embeddings, pgvector, hybrid search, NER

Data Pipelines

Apache Airflow, batch processing, data orchestration, JSON/unstructured parsing

Cloud & Databases

AWS (S3, EKS, Fargate, Glue, SQS), Aurora PostgreSQL, SQL

Nice to Have

• Experience building production RAG (Retrieval-Augmented Generation) applications and evaluation harnesses.
• Exposure to financial services, insurance claims, or legal document processing.
• Familiarity with database schema migration tools like Liquibase.