Junior Software Engineer (QA & Automation)
Description
This role is ideal for an early-career engineer excited to work on AI and data-driven products. You’ll help ensure the accuracy, consistency, and reliability of our systems while learning from senior engineers. As part of a small, collaborative team, you’ll test, validate, and automate workflows that make complex processes simple, repeatable, and reliable.
Flexible: 20–35+ hours/week
Core Responsibilities
Manual QA & Validation
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Test software pipelines and AI model outputs for accuracy, consistency, and stability.
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Develop and maintain automated validation scripts and regression test suites.
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Maintain and curate test datasets to ensure broad coverage of normal, edge, and failure scenarios.
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Assist in defining and documenting test plans, acceptance criteria, and QA results with product and engineering teams.
Automated Testing
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Write automated unit and integration tests using frameworks such as PyTest or Jest.
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Integrate automated tests into CI/CD pipelines (e.g., GitHub Actions, Jenkins) for repeatable QA workflows.
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Monitor test results and troubleshoot failures with guidance from senior engineers.
Configuration & Environment Management
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Apply and verify code and pipeline configurations following defined processes.
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Maintain configuration files, environment variables, and schema updates across test environments.
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Support setup of data mappings, schema definitions, and parameter configurations for new customers with guidance from senior engineers.
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Validate new customer configurations and sample outputs for accuracy and completeness.
Lightweight Development
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Implement minor bug fixes and small code enhancements as part of QA feedback.
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Contribute to code reviews and assist in refactoring or documentation.
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Collaborate on scripting and automation to streamline validation, deployment, or monitoring steps.
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Participate in team QA reviews and retrospectives to improve processes and automation coverage.
Required Skills & Experience
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1–3 years of professional experience in QA automation, software testing, or software engineering.
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Working knowledge of Python or similar scripting languages.
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Familiarity with unit testing frameworks (e.g., PyTest, Unittest, Mocha/Jest).
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Basic understanding of CI/CD tools (e.g., GitHub Actions, Jenkins, CircleCI).
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Experience with Git and modern source control workflows.
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Comfortable working with JSON schemas, API validation, and data-driven testing.
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Comfortable leveraging AI tools to augment and optimize day-to-day tasks.
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Strong attention to detail and process adherence.
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Comfortable working in small, fast-moving technical teams.
Ideal Candidate Traits
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Hands-on and detail-oriented, with the ability to thrive in a fast-moving startup environment.
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A “get it done” attitude and proven track record of taking ownership over workstreams.
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Comfortable managing priorities across multiple operational responsibilities.
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Collaborative and able to communicate effectively with both technical and non-technical stakeholders.
Nice to Haves
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Exposure to AI, ML, or data processing pipelines.
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Experience validating AI or ML model outputs (data extraction, classification, etc.).
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Experience with Docker or cloud-based environments.
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Familiarity with schema validation libraries and data transformation workflows.
Originally posted on Himalayas