Full Stack Developer
Software Engineer – Full Stack (SDE-1 / SDE-2)
About The Role
We are looking for a motivated and technically strong Software Engineer – Full Stack with 1–3 years of professional experience to join our engineering team.
The role involves building and maintaining full-stack applications, developing backend services and REST APIs, working with relational and NoSQL databases, and deploying and validating applications using Docker and containerized environments.
A significant part of the role will involve functional QA, automated testing, Docker image verification, debugging, and troubleshooting across the application stack. The engineer will also be expected to leverage AI-assisted development tools to improve engineering productivity across coding, debugging, testing, documentation, and technical research while maintaining ownership of code quality and correctness.
Key Responsibilities
Full-Stack Development
- Design, develop, and maintain production-ready frontend and backend applications.
- Build responsive and reusable frontend components using React, JavaScript, TypeScript, HTML, and CSS.
- Develop backend services using Python, Node.js, or similar technologies.
- Design, implement, and integrate RESTful APIs.
- Implement authentication, authorization, validation, error handling, and application-level business logic.
- Collaborate with engineers and product teams to translate requirements into scalable technical solutions.
Backend & Database Development
- Develop backend services and APIs using Python and/or Node.js.
- Work with relational databases such as PostgreSQL and MySQL.
- Work with NoSQL technologies such as MongoDB and Redis.
- Design database schemas following appropriate normalization and data modeling principles.
- Write efficient SQL queries and perform basic query optimization.
- Implement appropriate indexing, caching, and data-access patterns where required.
- Troubleshoot application, API, and database-related issues.
Docker & Containerization
- Develop, build, manage, and troubleshoot Docker container images.
- Create and maintain Dockerfiles for application and service deployment.
- Use Docker Compose for multi-container application environments.
- Validate container startup, service health, dependencies, networking, configuration, and runtime behavior.
- Perform Docker image verification to ensure images contain the required packages, configurations, permissions, dependencies, and application functionality.
- Troubleshoot container, image, networking, configuration, and environment-related issues.
- Support consistent development, testing, and deployment environments through containerization.
Testing & Quality Assurance
- Develop and execute functional, unit, integration, API, and regression tests.
- Implement automated testing for frontend and backend functionality.
- Validate APIs, application workflows, database interactions, and service integrations.
- Build automated validation workflows for Docker/container images.
- Verify image integrity, package availability, configurations, permissions, exposed services, dependencies, and runtime behavior.
- Identify, reproduce, debug, and document software defects.
- Analyze test failures and perform root-cause analysis.
- Improve test coverage and introduce regression tests for previously identified issues.
- Work closely with QA and engineering teams to improve overall product reliability.
Debugging & Production Support
- Investigate issues across the frontend, backend, API, database, Docker, and infrastructure layers.
- Analyze application logs, stack traces, API responses, database behavior, and container logs.
- Reproduce production and development issues and identify their root causes.
- Implement fixes while minimizing regression risk.
- Participate in production issue resolution and post-incident analysis.
- Collaborate with senior engineers on complex technical problems and architectural decisions.
AI-Assisted Engineering & Productivity
- Use AI-assisted development tools to improve engineering productivity and accelerate software development workflows.
- Leverage AI tools for:
- Code generation and implementation assistance
- Code understanding and exploration
- Debugging and error analysis
- Unit and integration test generation
- Test-case and edge-case identification
- Code review and refactoring
- Technical documentation
- API and library research
- Development workflow automation
- Use AI to analyze logs, stack traces, test failures, and unfamiliar codebases to accelerate troubleshooting