DevOps and Backend Internship
Deckoviz Space Labs
IndiaFresher6d agovia LinkedIn
About the Role
- 3-6 month paid internship, full-time.
- This role involves building, deploying, and managing production-grade applications.
- Hands-on experience with Python backend APIs, server deployments on AWS/GCP, database management, and optimizations.
Key Responsibilities
- Design, build, and deploy production-grade Python backend applications (FastAPI/Django).
- Manage end-to-end deployments on AWS/GCP cloud servers.
- Set up and optimize CI/CD pipelines.
- Work with SQL & NoSQL databases (PostgreSQL, MongoDB, Redis).
- Handle infrastructure monitoring, scaling, and troubleshooting.
- Contribute to the frontend (React/Next.js) when needed for end-to-end feature delivery.
- Maintain clean documentation and support sprint-based development cycles.
Requirements & Tech Stack
- Must be in the final year of college or have completed college.
- Strong proficiency in Python and frameworks like FastAPI/Django.
- Proven experience deploying full-stack apps on production servers.
- Solid knowledge of Linux-based server environments.
- Hands-on with cloud platforms (AWS/GCP/Azure).
- Experience with databases: PostgreSQL, MySQL, MongoDB (design, queries, scaling).
- Familiar with CI/CD tools (GitHub Actions, GitLab CI, Jenkins).
- Strong debugging, optimization, and problem-solving skills.
- Comfortable working independently in a fast-moving startup environment.
Bonus Points (Not Mandatory, But Appreciated)
- Docker, Kubernetes, or container orchestration experience.
- Infrastructure as Code (Terraform, Ansible).
- Strong frontend skills (React/Next.js, Tailwind).
- Security best practices in production systems.
- Prior startup or production-grade system experience.
Why Join Deckoviz?
- Real-world impact: Ship features and infra to production from Day 1.
- Internship → Full-Time Pathway: Exceptional performance can lead to a full-time role.
- Stipend: ₹5,000/month.
- Remote, flexible work culture.
- Ownership and autonomy in building, deploying, and managing live systems.
- Direct exposure to AI pipelines, cloud infra, and scalable systems.