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I am a Full-Stack AI Engineer who builds end-to-end products from React frontends to LLM-backed services and AWS cloud infrastructure. I enjoy turning ideas into scalable, observable systems with strong ownership and impact. My experience spans TypeScript, Python, Node.js, PostgreSQL/MySQL, and ML tooling, delivering pragmatic solutions in healthcare and AI-driven domains while collaborating across product, design, and ops teams.…I am a Full-Stack AI Engineer who builds end-to-end products from React frontends to LLM-backed services and AWS cloud infrastructure. I enjoy turning ideas into scalable, observable systems with strong ownership and impact. My experience spans TypeScript, Python, Node.js, PostgreSQL/MySQL, and ML tooling, delivering pragmatic solutions in healthcare and AI-driven domains while collaborating across product, design, and ops teams.

Agrima Jain

Full Stack Developer, Web Developer, AI Engineer, +2

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I am a Full-Stack AI Engineer who builds end-to-end products from React frontends to LLM-backed services and AWS cloud infrastructure. I enjoy turning ideas into scalable, observable systems with strong ownership and impact. My experience spans TypeScript, Python, Node.js, PostgreSQL/MySQL, and ML tooling, delivering pragmatic solutions in healthcare and AI-driven domains while collaborating across product, design, and ops teams.…I am a Full-Stack AI Engineer who builds end-to-end products from React frontends to LLM-backed services and AWS cloud infrastructure. I enjoy turning ideas into scalable, observable systems with strong ownership and impact. My experience spans TypeScript, Python, Node.js, PostgreSQL/MySQL, and ML tooling, delivering pragmatic solutions in healthcare and AI-driven domains while collaborating across product, design, and ops teams.

Available to hire

I am a Full-Stack AI Engineer who builds end-to-end products from React frontends to LLM-backed services and AWS cloud infrastructure. I enjoy turning ideas into scalable, observable systems with strong ownership and impact.

My experience spans TypeScript, Python, Node.js, PostgreSQL/MySQL, and ML tooling, delivering pragmatic solutions in healthcare and AI-driven domains while collaborating across product, design, and ops teams.

Skills

Experience Level

Expert

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Work Experience

Full Stack AI Engineer (Intern) at Amwell

June 1, 2025 - August 1, 2025

Engineered RAG pipelines in TypeScript over FHIR data using Postgres, Redis caching, and Claude/OpenAI APIs, cutting query latency by 40% and improving prediction accuracy by 35%. Designed event-driven scheduling workflows using RabbitMQ-backed async job orchestration and pub/sub patterns with Redis state, reducing manual coordination by 30% across clinical operations. Automated healthcare scheduling by implementing agentic AI workflows on AWS Lambda, delivering WebSocket-based real-time updates to notify clients of scheduling changes and reducing manual effort by 50% for 10,000+ users. Architected AWS CloudWatch dashboards to track daily API calls and performance metrics.

Software Engineer at HappyMonk AI Labs

August 1, 2022 - November 1, 2023

Delivered user-facing features including authentication, data visualizations, and workflow management using React frontend and Node.js/NestJS backend with Prisma ORM and MySQL, achieving 20% lower latency and 50% higher throughput. Designed a distributed notification system using AWS SQS for asynchronous processing, Amazon SES for email notifications, and load balancing with rate limiting to maintain system stability at scale. Architected a full-stack face re-identification system with interactive UI and event-driven Node.js/TypeScript backend processing 128-point embeddings with Postgres, enhancing accuracy by 18%. Containerized backend services by creating Docker images, using Docker Compose for local development, and deploying microservices to Kubernetes clusters in production.

Associate Software Engineer at HappyMonk AI Labs

January 1, 2021 - July 1, 2022

Constructed license plate detection model with YOLOv5 and OCR-based recognition, preprocessing 36 characters for 95% accuracy and 20% speed gain, with UI built using HTML, CSS, and JavaScript. Created an LLM-driven text extraction and summarization pipeline for OCR outputs and unstructured metadata, automating tagging for 100k+ image records and reducing manual search effort by 50%. Redesigned MLOps pipelines, working with the product team to align model workflows with backend systems using RabbitMQ, Kafka-based pub/sub, and CI/CD, improving validation efficiency by 22%.