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

• Test software pipelines and AI model outputs for accuracy, consistency, and stability.

• Develop and maintain automated validation scripts and regression test suites.

• Maintain and curate test datasets to ensure broad coverage of normal, edge, and failure scenarios.

• Assist in defining and documenting test plans, acceptance criteria, and QA results with product and engineering teams.

Automated Testing

• Write automated unit and integration tests using frameworks such as PyTest or Jest.

• Integrate automated tests into CI/CD pipelines (e.g., GitHub Actions, Jenkins) for repeatable QA workflows.

• Monitor test results and troubleshoot failures with guidance from senior engineers.

Configuration & Environment Management

• Apply and verify code and pipeline configurations following defined processes.

• Maintain configuration files, environment variables, and schema updates across test environments.

• Support setup of data mappings, schema definitions, and parameter configurations for new customers with guidance from senior engineers.

• Validate new customer configurations and sample outputs for accuracy and completeness.

Lightweight Development

• Implement minor bug fixes and small code enhancements as part of QA feedback.

• Contribute to code reviews and assist in refactoring or documentation.

• Collaborate on scripting and automation to streamline validation, deployment, or monitoring steps.

• Participate in team QA reviews and retrospectives to improve processes and automation coverage.

Required Skills & Experience

• 1–3 years of professional experience in QA automation, software testing, or software engineering.

• Working knowledge of Python or similar scripting languages.

• Familiarity with unit testing frameworks (e.g., PyTest, Unittest, Mocha/Jest).

• Basic understanding of CI/CD tools (e.g., GitHub Actions, Jenkins, CircleCI).

• Experience with Git and modern source control workflows.

• Comfortable working with JSON schemas, API validation, and data-driven testing.

• Comfortable leveraging AI tools to augment and optimize day-to-day tasks.

• Strong attention to detail and process adherence.

• Comfortable working in small, fast-moving technical teams.

Ideal Candidate Traits

• Hands-on and detail-oriented, with the ability to thrive in a fast-moving startup environment.

• A “get it done” attitude and proven track record of taking ownership over workstreams.

• Comfortable managing priorities across multiple operational responsibilities.

• Collaborative and able to communicate effectively with both technical and non-technical stakeholders.

Nice to Haves

• Exposure to AI, ML, or data processing pipelines.

• Experience validating AI or ML model outputs (data extraction, classification, etc.).

• Experience with Docker or cloud-based environments.

• Familiarity with schema validation libraries and data transformation workflows.

Originally posted on Himalayas