QA Engineer
Company shown to members 🔒 · Remote · Singapore, Hong Kong only
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First recorded by Psst: 9 November 2026. The company's name and the apply link are for Psst members, from $4.99 for 7 days.
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The 20-second read
- Experience
- 3+ years required
- Where you can live
- Singapore, Hong Kong only
- Skills and tools
- python, java, qa
- Degree or licence
- Mentioned (bachelor's)
- Job type
- Full-time
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Job details
- Where you can work
- Singapore, Hong Kong
- Employment type
- Full-time
- Advertised pay
- Not stated by the employer
- Experience
- 3+ years required
- Employer publication date
- 30 June 2026
- First recorded by Psst
- 9 November 2026
- Last checked at the source
- 10 November 2026
About the job
Responsibilities
Own the full software testing and release lifecycle—requirement analysis, risk assessment, test design and execution, defect tracking, and release verification—where testing is now largely driven by AI.
Maintain and evolve these AI skill/agent pipelines to continuously improve defect detection while preventing escaped defects, and drive broader adoption of intelligent analysis and workflow automation across the team.
Requirements
Bachelor's degree in Computer Science, Software Engineering, or related field
Proficiency in at least one programming language (Go/Rust/Python/Java)
3 to 7 years of QA or Dev-in-Test experience in Internet/Fintech industry
Understanding of different testing categories: Function, Performance, Stability, and Chaos Engineering
Strong problem-solving skills with the ability to break down and resolve complex technical issues
Self-driven with a strong sense of urgency and commitment to learning and professional growth
[Bonus] Familiarity with EVM-compatible blockchains—including the execution model (EVM opcodes, gas metering, state transitions); transaction lifecycle (mempool, ordering, block inclusion, finality); and common failure and edge cases (chain reorgs, nonce/gas errors, consensus divergence, state-sync issues)—especially with hands-on experience testing node clients or protocol-level components.
[Bonus] Hands-on experience applying AI/LLM to testing workflows—prompt engineering, building or maintaining agent/skill pipelines, and evaluating AI-generated test artifacts.
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