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Salary: USD 90,000 - 120,000 / annual
ZEFR is hiring a Software Development Engineer in Test (SDET) to help own quality across APIs, web apps, data pipelines, and AI-powered services. You'll work inside product engineering teams, treating testing as a software problem and focusing on code-based automation rather than manual test scripts.
Key responsibilities include:
- Plan testing for each feature by joining grooming sessions, asking clarifying questions, and writing comprehensive test plans covering happy paths, edge cases, and negative cases.
- Build and maintain test automation for REST and GraphQL APIs, backend services, web UIs, and third-party partner APIs using a shared code-based framework. Review teammates' test code.
- Validate data pipelines and data quality by writing checks on pipeline outputs (schemas, row counts, freshness, business rules) and helping define data SLAs.
- Test AI and ML features, including comparing model or prompt versions on fixed datasets, validating shadow deployments before rollout, and testing AI agents and their tools for correct behavior, input validation, and error handling.
- Keep tests running in CI/CD by wiring suites into pipelines so they gate merges and deploys, ensuring they remain fast and reliable.
- Validate releases in preview, staging, and production environments: prepare test data, run regression tests, sign off, and verify after deployment.
- Monitor production quality by building synthetic checks, dashboards, and alerts that catch regressions and bad data before customers do.
- Investigate issues and incidents by reproducing problems, finding root causes, writing clear bug reports, and verifying fixes. Help during high-severity incidents.
- Work across roles with engineers, product managers, data scientists, and customer-facing teams. Turn findings into well-scoped tickets and share quality status openly.
ZEFR is headquartered in Los Angeles with global offices in New York, Chicago, London, Toronto, Singapore, and more. The company is the leader in AI-powered content classifications for brands and advertisers, with a platform purpose-built for multi-modal content understanding on open platforms like YouTube, TikTok, Meta, and Snap.
REQUIREMENTS:
- 1–3 years of experience, ideally as a QA engineer or SDET, with hands-on test automation.
- Solid coding skills in at least one language used for test automation. Python is preferred; Java, TypeScript, or Go also work.
- Experience automating API tests: request and response validation, schema checks, and negative cases.
- Experience with a modern UI end-to-end framework such as Playwright, Cypress, or Selenium.
- Working SQL knowledge. You can query across tables to confirm data is complete and correct.
- Good test design instincts: edge cases, boundary values, negative cases, and the test pyramid.
- Comfort with Git, pull requests, code review, and running tests in CI/CD pipelines.
- Persistence when debugging: reading logs, inspecting network calls, and querying databases.
- Clear written communication: bug reports, test plans, and short async status updates.
NICE TO HAVE:
- Exposure to a public cloud (GCP, AWS, or Azure) and containers.
- Testing data pipelines and orchestration tools (Airflow, dbt, Great Expectations, Elementary) or data warehouses (Snowflake, BigQuery).
- Testing ML models or LLM-powered features, including evaluation datasets and handling non-deterministic outputs.
- Testing AI agents or MCP servers, or using AI coding assistants to speed up test writing and exploratory testing.
- Observability and alerting tools (Datadog, Grafana, Cloud Monitoring, PagerDuty) and synthetic monitoring.
- Performance and load testing (k6, Locust, JMeter).
- Experience with ad tech, digital media, or large third-party platform APIs (Google Ads, Meta, TikTok, Snap).
- Frontend knowledge (React) to test framework upgrades and migrations.
- Security basics for test environments, such as managing secrets for test accounts.
