Full Stack Python Developer

1. Full Stack Developer (Python-Heavy) Internal Platform

Location: Bengaluru, India

Experience: 5–8 years

Team: Platform Engineering

About the Role

We are building the internal platform our engineering teams use every day — self-service infrastructure provisioning, cost visibility, approval workflows, and automation tooling. You will own features end to end: the API and business logic in Python, the interface engineers actually click through, and the integrations that tie it into our CI/CD and cloud stack.

This is a product-minded engineering role with a captive user base. Your users sit in the same building, feedback arrives the same week, and you will see the impact of what you ship within days. If you like owning a surface area rather than a ticket queue, this is that role.

What You Will Do

• Design and build full-stack features — Python services on the backend, modern JavaScript/TypeScript on the frontend.
• Build and maintain REST APIs that power internal portals, chat-based interfaces, and automation workflows.
• Integrate with cloud provider APIs (GCP/Azure), Azure DevOps, GitLab, Jira, and chat platforms to automate manual engineering workflows.
• Model and query relational data (PostgreSQL) with an eye on performance and correctness.
• Write tests, participate in code reviews, and keep the deployment pipeline healthy.
• Partner with DevOps and SRE to containerize, deploy, and observe what you build.
• Translate ambiguous internal requirements into scoped, shippable increments — and push back when the ask is unclear.

Must-Have Skills

• 5+ years of professional software development, with strong depth in Python (FastAPI, Django, or Flask).
• Solid frontend experience with React (or Vue/Angular) — component design, state management, consuming REST APIs.
• Strong grasp of REST API design, authentication/authorization patterns (OAuth2, JWT, SSO).
• Working knowledge of SQL and relational schema design.
• Git-based workflows and experience with CI/CD pipelines (Azure DevOps, GitLab).
• Comfortable with Docker and reading/writing YAML-driven configuration.
• Clear written communication — you can document a design and defend a decision.

Good to Have

• Kubernetes exposure (debugging your own services).
• Familiarity with LLM APIs or building Agents AI.
• Async Python (asyncio, Celery, message queues).
• Observability tooling — Prometheus, Grafana, structured logging.Role & responsibilities

Preferred candidate profile