Senior Python Developer

SID Global Solutions; Bengaluru; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

SID Global Solutions in Bengaluru is seeking an experienced Python + GenAI Developer to build scalable backend services using Python, FastAPI, Django and integrate AI-powered solutions with LLMs.

You will work with AWS, containers (Docker/Kubernetes), and modern DevOps practices to deliver secure, reliable AI-enabled applications for Financial Services and Banking domain.

Qualifications

• Proficient Python backend development
• Hands-on with FastAPI and Django
• Experience building AI-powered apps with LLMs
• Exposure to Google ADK, LangChain or similar frameworks
• Experience with AWS cloud services and container orchestration
• Knowledge of REST APIs, microservices and CI/CD practices
• Experience with Redis and datastores (SQL/NoSQL)
• Secure API development and enterprise integrations in BFSI domain (advantage)

Responsibilities

• Design, develop, and maintain scalable backend apps using Python, FastAPI, and Django.
• Build and integrate RESTful APIs and microservices.
• Develop AI-powered apps and intelligent agents with LLMs.
• Implement AI workflows with Google ADK or similar frameworks.
• Deploy cloud-native apps on AWS and containerize with Docker.
• Use Kubernetes/Helm for deployment and orchestration.
• Implement CI/CD and DevOps best practices.
• Design relational and NoSQL databases, optimize queries and indexing.
• Apply Redis caching to improve performance.
• Troubleshoot production issues for reliability and security.

Skills

Python

FastAPI

Django

Generative AI

LLMs

AWS

Docker

Kubernetes

REST APIs

Microservices

AsyncIO

Tools

LangChain

LangGraph

Google ADK

Terraform

Job description

Job Description - Python + GenAI Developer

Role: Python + GenAI Developer

Domain: Banking / BFSI

Employment Type: Full-Time

Role Overview

We are looking for an experienced Python + GenAI Developer with strong hands-on experience in Python backend development, FastAPI, Django, and Generative AI technologies. The ideal candidate should have practical experience building AI-powered applications, conversational AI solutions, intelligent agents, and scalable backend services.

Candidates should have hands-on exposure to Google ADK, Agentic AI frameworks, LLM integrations, AWS cloud services, and containerized application deployment.

Key Responsibilities

• Design, develop, and maintain scalable backend applications using Python, FastAPI, and Django.
• Build and integrate RESTful APIs and backend microservices.
• Develop AI-powered applications, conversational AI solutions, and intelligent AI agents using LLMs.
• Implement Agentic AI workflows and orchestration using Google ADK or similar frameworks.
• Integrate LLMs with enterprise applications and external services.
• Develop asynchronous applications using Python AsyncIO.
• Deploy and manage cloud-native applications using AWS services.
• Containerize applications using Docker and deploy them using Kubernetes and Helm.
• Implement CI/CD pipelines and follow DevOps best practices.
• Design and optimize relational and NoSQL databases, including indexing, query optimization, and connection pooling.
• Implement Redis caching strategies to improve application performance.
• Follow clean architecture, object-oriented programming, design patterns, and coding best practices.
• Troubleshoot production issues and ensure application scalability, reliability, and security.

Required Technical Skills

• Strong hands-on experience in Python programming.
• Good experience with FastAPI and Django.
• Strong understanding of REST API development and microservices architecture.
• Hands-on experience with Generative AI, LLMs, and Agentic AI.
• Experience with Google ADK, LangChain, LangGraph, or similar AI frameworks.
• Experience building AI agents, conversational AI, and workflow orchestration systems.
• Strong experience with AWS cloud services.
• Hands-on experience with Docker, Kubernetes, and Helm.
• Knowledge of CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI.
• Strong knowledge of SQL and NoSQL databases.
• Experience with Redis and caching mechanisms.
• Good understanding of Python AsyncIO and asynchronous programming.

Banking / BFSI Domain Experience

• Experience working on Banking, BFSI, Financial Services, or FinTech applications.
• Understanding of banking workflows, financial transactions, and enterprise integrations.
• Exposure to secure API development, authentication, authorization, and data protection.
• Experience developing AI-powered solutions for banking or financial services is an added advantage.

Preferred Skills

• Experience with RAG (Retrieval-Augmented Generation).
• Exposure to vector databases such as Pinecone, FAISS, ChromaDB, or Milvus.
• Experience with AWS Bedrock or other enterprise LLM platforms.
• Knowledge of LLM security, prompt engineering, and responsible AI practices.
• Experience deploying and monitoring production-grade GenAI applications.