Gen AI developer

We are seeking an experienced Senior Full Stack Developer (10+ years) to work on AI-

powered and Generative AI (GenAI) solutions. The ideal candidate must have deep

expertise primarily in Python along with experience in Python-based frameworks like

LangChain, LangGraph, and FastAPI. Good knowledge in Java, Angular, JavaScript,

HTML, and CSS is preferred for end to end implementation . Additionally, the candidate

must possess strong knowledge of Generative AI ecosystems. Experience with LLM-

based applications, prompt engineering, and cloud services such AWS Bedrock or

OpenAI LLM stack is a must. Exposure to AWS services is a strong advantage.

Key Responsibilities:

Develop and optimize AI-powered applications using LangChain, LangGraph,

and FastAPI.

Design, develop, and maintain scalable web applications with Angular,

JavaScript, HTML, and CSS.

Build microservices and RESTful APIs using FastAPI, and Python. (Java comes

a secondary if using Spring AI eco system )

Integrate and interact with LLMs (Large Language Models) using AWS

Bedrock/OpenAI.

Implement prompt engineering strategies to fine-tune LLM outputs.

Should be knowing the optimization technique while implementing a scalable

Gen AI solution in Cloud

Ensure cloud-ready architectures with AWS services like Lambda, S3, API

Gateway, and DynamoDB.

Required Skills:

Python & Frameworks: Deep expertise in LangChain, LangGraph, FastAPI,

(Flask, Django exposure is good to have in case LangChain / Langgraph

exposure is limited).

Working knowledge of Java is preferred to understand the current code eco

system as we often plug the Gen AI code in current Java code base.

LLM & Prompt Engineering: Hands-on experience with LLM interactions, prompt

tuning, OpenAI/AWS Bedrock.

Frontend Development: Proficiency in Angular, JavaScript, HTML, CSS for

interactive UI/UX.

Backend Development: Experience with Java & Python-based microservices and

APIs.

Cloud Exposure (AWS Preferred): Familiarity with AWS Bedrock, OpenAI APIs,

S3, Lambda, DynamoDB, EC2.

Databases: SQL (PostgreSQL, MySQL) & NoSQL (MongoDB, QDrant).

Good to have:

AI & ML Concepts: Strong understanding of ML algorithms,

supervised/unsupervised learning, GenAI ecosystem.

Python based framework -Django/Flask exposure

Java-for plugging in solution in current Java based eco system