Python Fullstack Engineer
Summary
Lead full-stack engineer driving a high-performance pod: builds scalable web apps with Python backends (FastAPI/Django/Flask) and React.js/Angular frontends, owns low-level design, CI/CD, Docker/Kubernetes and cloud IaC, and mentors developers. Full-time, onsite in Chennai, 6+ years' experience required.
Python Fullstack Engineer
Location: Chennai, TN
Job Type: Full-time
Education: BE CS, MCA, M.Sc. CS, M.Sc./B. Tech IT (4+ years of technical education required)
Experience: 6+ years
Role Overview
As a Lead Engineer, you will be the primary technical driver for a high-performance engineering pod. You will specialize in building scalable web applications using Python and modern frontend frameworks like React.js or Angular. This role demands a "Player-Coach" mentality—balancing deep technical execution (coding and system design) with the mentorship of developers. You will oversee the full software development lifecycle, from UI component architecture to DevOps automation and cloud deployment.
Key Responsibilities
Full-Stack Architecture & Development
- Frontend Excellence: Lead the development of responsive, high-performance user interfaces using React.js or Angular. Ensure component reusability and state management best practices (Redux, Context API, RxJS).
- Python Backend Mastery: Design and maintain scalable server-side logic using frameworks like FastAPI, Django, or Flask.
- Design Ownership: Create and maintain Low-Level Designs (LLD), including API contracts (Swagger/OpenAPI), database schemas, and frontend component hierarchies.
- PoC & Prototyping: Rapidly build Proof of Concepts to validate new features, UI/UX flows, or third-party integrations.
DevOps & Automation
- CI/CD Integration: Drive the automation of builds and deployments using GitHub Actions, Jenkins, or GitLab CI.
- Containerization: Ensure all services are containerized using Docker and orchestrated via Kubernetes (AKS/EKS).
- Infrastructure as Code: Work with Terraform or CloudFormation to manage cloud-native environments.
AI & Specialized Automation (Integrated Focus)
- AI-Enabled Features: Implement Python-based integration for AI services (OpenAI SDKs, LangChain) into the application layer.
- Process Automation: Use Python for scripting and task automation to improve internal team velocity and system reliability.
Technical Leadership & Agile
- Code Mentorship: Conduct deep-dive code reviews to ensure compliance with LLD and high-quality standards.
- SprintManagement: Lead Story Point estimation and Sprint Planning. Translate complex business requirements into clear technical tasks for the team.
