Full Stack AI Engineer

Hind Industec; Pune District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Hind Industec in Pune is seeking a talented full-stack engineer to build web apps, APIs, and AI-powered systems. You will work on LLM-enabled workflows, embeddings, vector search, and on-prem inference using vLLM or SGLang.

Collaboration with product, design, and engineering teams is key. Applicants should have strong Python experience with FastAPI/Django/Flask, React frontend skills, and a solid grounding in testing, security, and scalable software practices.

Qualifications

• Professional experience building full-stack web applications.
• Strong Python skills with modern web frameworks.
• Experience designing REST APIs or service interfaces.
• Hands-on experience with LLM-powered applications and RAG workflows.
• Familiarity with function calling, MCP, and AI tooling design.
• Knowledge of embeddings, vector search, and document-processing pipelines.
• Experience with PostgreSQL and at least one vector database or vector search.
• Frontend experience with JavaScript/TypeScript and React.
• Familiarity with Git, automated testing, deployment workflows, and best practices.
• Strong problem-solving, communication, and collaboration skills.

Responsibilities

• Build and maintain web applications, APIs, and services using Python.
• Develop and improve AI applications using LLMs, including RAG solutions.
• Design document-ingestion, chunking, embedding, retrieval, and response workflows.
• Design and develop tools for AI applications, including function-calling workflows and MCP integrations.
• Integrate vector databases and search into production systems.
• Develop responsive frontend features and connect them to backend APIs.
• Evaluate AI output quality, retrieval relevance, latency, and cost; improve performance.
• Implement authentication, authorization, logging, testing, and monitoring.
• Apply SOLID principles and design patterns for scalable systems.
• Deploy and operate LLMs on-premises using inference servers such as vLLM or SGLang.
• Collaborate with product, design, and engineering to turn requirements into features.
• Document technical decisions and contribute to code reviews and standards.

Skills

Full-stack development

Python

REST APIs

LLM apps

RAG workflows

Embeddings

Vector search

PostgreSQL

React

Git

Testing

CI/CD

Security

Problem-solving

Communication

AWS

Azure

Google Cloud

Docker

MCP

vLLM

SGLang

Tools

FastAPI

Django

Flask

React

PostgreSQL

Vector DB

Docker

CI/CD tooling

MCP

vLLM

SGLang

Job description

Responsibilities

• Build and maintain web applications, APIs, and services using Python.


• Develop and improve AI applications using large language models (LLMs), including Retrieval-Augmented Generation (RAG) solutions.


• Design document-ingestion, chunking, embedding, retrieval, and response-generation workows.


• Design and develop tools for AI applications, including function-calling workows and integrations using the Model Context Protocol (MCP).


• Integrate vector databases and search technologies into production systems.


• Develop responsive frontend features and connect them to backend APIs.


• Evaluate AI output quality, retrieval relevance, latency, and cost; improve performance and reliability.


• Implement authentication, authorization, logging, testing, and monitoring.


• Apply software engineering best practices, including SOLID principles and design patterns, to build scalable, maintainable systems.


• Deploy and operate LLMs in on-premises environments using inference servers such as vLLM or SGLang.


• Collaborate with product, design, and engineering teams to turn requirements into production-ready features.


• Document technical decisions and contribute to code reviews and engineering standards.

Required Qualications

• Professional experience developing full-stack web applications.


• Strong Python skills and experience with frameworks such as FastAPI, Django, or Flask.


• Experience designing and building REST APIs or similar service interfaces.


• Hands-on experience developing LLM-powered applications and RAG workows.


• Familiarity with function calling, MCP, and designing or developing tools for AI applications.


• Familiarity with embeddings, vector search, prompt design, and document-processing pipelines.


• Experience with a relational database such as PostgreSQL and at least one vector database or vector-search solution.

Frontend experience with JavaScript or TypeScript and a modern framework such as React.

Familiarity with Git, automated testing, deployment workows, and software engineering best practices.

Strong problem-solving, communication, and collaboration skills.

Preferred Qualications

• Experience with cloud platforms such as AWS, Azure, or Google Cloud.


• Familiarity with Docker, CI/CD, and production observability.


• Experience deploying LLMs on-premises, including using inference servers such as vLLM or SGLang.


• Experience with LLM evaluation, guardrails, hybrid search, reranking, or agentic workows.


• Experience handling sensitive data and implementing security and privacy controls.


• Contributions to technical projects, open-source software, or developer communities.