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