Sr. Python Developer

Role Overview

We are looking for an experienced Senior Python Developer to lead the design and development of scalable, high-performance backend applications and distributed systems. The ideal candidate should possess deep expertise in Python, backend architecture, API development, cloud technologies (AWS preferred), and modern software engineering practices.

The role requires technical leadership, mentoring junior developers, driving architectural decisions, and collaborating closely with product managers, architects, DevOps, and QA teams to deliver enterprise-grade solutions.

Key Responsibilities

• Design, develop, and maintain scalable, secure, and highly available Python applications.
• Architect backend systems, microservices, and RESTful APIs following industry best practices.
• Lead technical design discussions and drive architectural decisions.
• Review code and ensure adherence to coding standards, security guidelines, and engineering best practices.
• Optimize application performance, scalability, reliability, and cost efficiency.
• Design database schemas and optimize complex SQL queries.
• Collaborate with cross-functional teams to define technical solutions and implementation strategies.
• Mentor junior developers through code reviews, technical guidance, and knowledge sharing.
• Troubleshoot complex production issues and perform root cause analysis.
• Drive automation through CI/CD pipelines and Infrastructure as Code.
• Ensure applications are observable through proper logging, monitoring, and alerting.
• Participate in Agile ceremonies and contribute to sprint planning and technical estimation.

Required Technical Skills

Programming & Backend:
Expert-level Python programming experience.
Strong experience with FastAPI, Flask, or Django.
Extensive experience designing and developing RESTful APIs.
Strong understanding of Object-Oriented Programming (OOP), SOLID principles, and design patterns.
Experience building scalable microservices architectures.
Strong understanding of asynchronous programming.

Databases:
Strong knowledge of relational databases such as PostgreSQL, MySQL, or SQL Server.
Experience with NoSQL databases such as MongoDB, DynamoDB, or Redis.
Ability to optimize complex SQL queries and database performance.

Cloud (Preferred):
Hands-on experience with AWS services including Lambda, ECS, EC2, S3, API Gateway, CloudWatch, IAM, SQS/SNS, RDS. Exposure to Azure or GCP is an added advantage.

DevOps & Deployment:
Docker and containerized application development.
Kubernetes fundamentals.
CI/CD using GitHub Actions, Jenkins, GitLab CI, or AWS CodePipeline.
Experience with Linux environments.

Software Engineering

• Git and modern branching strategies.
• Unit, integration, and end-to-end testing (PyTest, Unittest).

Good to Have

• Experience developing AI/ML or Generative AI applications.
  Exposure to LLM frameworks such as LangChain, LangGraph, or LlamaIndex.
  Experience integrating with vector databases.