Python Backend Developer

SP Software; Hyderabad; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

SP Software is seeking an experienced Python developer to design and deploy AI-powered APIs using FastAPI and LLM-based solutions. The role emphasizes building scalable backend services, web scraping workflows, and integrating AI components with enterprise systems.

The ideal candidate has hands-on experience with Docker/Kubernetes, databases (MongoDB, MS SQL), and knowledge of RAG, prompt engineering, and AI frameworks like LangChain or FAISS.

Qualifications

• Strong Python development experience (5 years).
• Experience developing APIs using FastAPI, Flask, or Django.
• Hands-on experience with Generative AI and LLMs (OpenAI, Azure OpenAI, Gemini, Claude, or open-source models).
• Experience building RAG applications with embeddings, semantic and hybrid search.
• Strong understanding of Prompt Engineering.
• Experience with AI frameworks such as LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or LangGraph.
• Experience with MongoDB and MS SQL Server.
• Hands-on experience with Selenium, BeautifulSoup, or Scrapy for web scraping and data extraction.
• Experience with Docker and Kubernetes for containerized deployments.
• Strong understanding of REST APIs, software design principles, and system integration.

Responsibilities

• Design, develop, and deploy AI-powered applications using LLMs and Generative AI technologies.
• Develop scalable Python-based APIs and backend services.
• Integrate AI solutions with enterprise applications, databases, and external systems.
• Develop document ingestion, indexing, retrieval, and knowledge management pipelines.
• Build web scraping and automated data collection solutions.
• Deploy, monitor, and optimize applications using Docker and Kubernetes.
• Ensure application scalability, security, reliability, and performance.
• Collaborate with cross-functional teams to deliver AI-driven business solutions.
• Stay current with evolving AI technologies, frameworks, and industry best practices.

Skills

Python development

APIs with FastAPI

LLMs & Generative AI

RAG applications

Prompt engineering

AI frameworks

MongoDB

MS SQL Server

Web scraping

Docker

Kubernetes

REST APIs

Tools

FastAPI

Flask

Django

MongoDB

MS SQL Server

Selenium

BeautifulSoup

Scrapy

Docker

Kubernetes

LangChain

LlamaIndex

Semantic Kernel

CrewAI

AutoGen

LangGraph

OpenAI

Azure OpenAI

Job description

Role & responsibilities

Mandatory Skills- Python (3-5 years), Develop APIs using FastAPI, LLM sdk, with python, MongoDB and MS SQL Server, Strong understanding of REST APIs and software design principles

• Strong Python development experience (5 years).


• Experience developing APIs using FastAPI, Flask, or Django.


• Hands-on experience with Generative AI and LLMs (OpenAI, Azure OpenAI, Gemini, Claude, or open-source models).


• Experience building RAG (Retrieval-Augmented Generation) applications with knowhow of Embeddings, Semantic and Hybrid search and Vectors


• Strong understanding of Prompt Engineering.


• Experience with AI frameworks such as LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or LangGraph.


• Experience with MongoDB and MS SQL Server.


• Hands-on experience with Selenium, BeautifulSoup, or Scrapy for web scraping and data extraction.


• Experience with Docker and Kubernetes for containerized deployments.


• Strong understanding of REST APIs, software design principles, and system integration.

Preferred Skills

• LLM sdk, with python service integration


• AI Agent and multi-Agent application development.


• Experience with Vector Databases such as PGVector or FAISS.


• NLP and document processing experience.


• Conversational AI development.

Key Responsibilities

• Design, develop, and deploy AI-powered applications using LLMs and Generative AI technologies.


• Develop scalable Python-based APIs and backend services.


• Integrate AI solutions with enterprise applications, databases, and external systems.


• Develop document ingestion, indexing, retrieval, and knowledge management pipelines.


• Build web scraping and automated data collection solutions.


• Deploy, monitor, and optimize applications using Docker and Kubernetes.


• Ensure application scalability, security, reliability, and performance.


• Collaborate with cross-functional teams to deliver AI-driven business solutions.


• Stay current with evolving AI technologies, frameworks, and industry best practices.