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:
o Code generation and implementation assistance
o Code understanding and exploration
o Debugging and error analysis
o Unit and integration test generation
o Test-case and edge-case identification
o Code review and refactoring
o Technical documentation
o API and library research
o Development workflow automation
· Use AI to analyze logs, stack traces, test failures, and unfamiliar codebases to accelerate troubleshooting