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.
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Build responsive and reusable frontend components using React, JavaScript, TypeScript, HTML, and CSS.
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Develop backend services using Python, Node.js, or similar technologies.
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Design, implement, and integrate RESTful APIs.
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Implement authentication, authorization, validation, error handling, and application-level business logic.
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Collaborate with engineers and product teams to translate requirements into scalable technical solutions.
Backend & Database Development
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Develop backend services and APIs using Python and/or Node.js.
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Work with relational databases such as PostgreSQL and MySQL.
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Work with NoSQL technologies such as MongoDB and Redis.
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Design database schemas following appropriate normalization and data modeling principles.
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Write efficient SQL queries and perform basic query optimization.
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Implement appropriate indexing, caching, and data-access patterns where required.
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Troubleshoot application, API, and database-related issues.
Docker & Containerization
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Develop, build, manage, and troubleshoot Docker container images.
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Create and maintain Dockerfiles for application and service deployment.
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Use Docker Compose for multi-container application environments.
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Validate container startup, service health, dependencies, networking, configuration, and runtime behavior.
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Perform Docker image verification to ensure images contain the required packages, configurations, permissions, dependencies, and application functionality.
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Troubleshoot container, image, networking, configuration, and environment-related issues.
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Support consistent development, testing, and deployment environments through containerization.
Testing & Quality Assurance
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Develop and execute functional, unit, integration, API, and regression tests.
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Implement automated testing for frontend and backend functionality.
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Validate APIs, application workflows, database interactions, and service integrations.
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Build automated validation workflows for Docker/container images.
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Verify image integrity, package availability, configurations, permissions, exposed services, dependencies, and runtime behavior.
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Identify, reproduce, debug, and document software defects.
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Analyze test failures and perform root-cause analysis.
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Improve test coverage and introduce regression tests for previously identified issues.
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Work closely with QA and engineering teams to improve overall product reliability.
Debugging & Production Support
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Investigate issues across the frontend, backend, API, database, Docker, and infrastructure layers.
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Analyze application logs, stack traces, API responses, database behavior, and container logs.
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Reproduce production and development issues and identify their root causes.
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Implement fixes while minimizing regression risk.
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Participate in production issue resolution and post-incident analysis.
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Collaborate with senior engineers on complex technical problems and architectural decisions.
AI-Assisted Engineering & Productivity
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Use AI-assisted development tools to improve engineering productivity and accelerate software development workflows.
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Leverage AI tools for:
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Code generation and implementation assistance
-
Code understanding and exploration
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Debugging and error analysis
-
Unit and integration test generation
-
Test-case and edge-case identification
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Code review and refactoring
-
Technical documentation
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API and library research
-
Development workflow automation
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Use AI to analyze logs, stack traces, test failures, and unfamiliar codebases to accelerate troubleshooting
