QA Engineer
Estimated AI exposure rank
38/100
Estimated range 31–44/100
Tests software quality through manual and automated testing strategies
QA Engineer has an estimated AI Exposure Rank of 38/100 — higher than 38% of official occupations. It is a synthetic blend of 3 occupations, not a job-loss probability.
Relative AI exposure, not a prediction of job loss. Hiring, wages and role design depend on many forces that this estimate does not forecast.
Limited current buffers in the supporting context.
Built from 3 official occupations in Singapore
Why This Score
84% of tasks overlap with current AI
24% human advantage from judgment & presence
60% demand buffer from the local labour market
On the Shortage Occupation List & Jobs in Demand list — government recognises hiring need
These factors interact with each other — the final score is not a simple sum of these bars.
Blended across 3 occupations using the same score logic as an occupation page. How this works
Tasks AI can handle
Code generation, test writing, documentation, code review suggestions, and debugging common patterns.
Where humans stay essential
System architecture decisions, complex debugging in production, cross-team coordination, requirements gathering, and security-critical code review.
Skills to focus on
Role profile
Heuristic workflow context blended from related occupations. This profile helps interpret the score; it is not a direct role-level measurement and is not part of the core net-risk formula.
Workflow dimensions (0 = low, 1 = high)
Singapore Now
Use these signals as directional context from closely related occupations and recent postings.
Observed hiring
0
30-day postings · no_signal
Employer signals
moderate
10 recent signals
Local support
1
blended context anchors
Top Industries
How this changes by career stage
What You Can Do
This estimated role shows some offset potential, but it depends on demand and transition pathways holding up across the blended occupation set.
Published transition support
Component occupation pathways
Explore each occupation for seniority and labour-market detailCompare with similar roles or occupations
Compare with... →Built From
Augmentation
Very Low (12%)
Dispersion
2.1pp spread · 31/100–44/100 range
Raw Scores
Exp 0.836 · Bot 0.240 · Mkt 0.601
Percentile Rank
More exposed than approximately 38% of occupations
Common tools in similar work
Blended from O*NET matches across 1 component occupations.
What helps
- A meaningful share of the work can likely be reorganized around AI rather than removed outright.
What could slow it down
- Current demand support is thin, so offsets may take longer to show up.
Worker profile
Gender mix
70% male / 30% femalePublished Singapore worker composition for blended detailed occupation-family anchors.
Employment structure
Employee-heavy96% employees, 4% employers or self-employed workers.
Work arrangement
Mostly full-time4% part-time and 96% full-time in 2025.
Age profile
Mid-career heavy14% aged 15 to 29, 62% aged 30 to 49, and 24% aged 50 or older.
Qualification mix
Degree-heavyDegree 81%; Diploma / professional qualification 15%.
Where this work is concentrated
Top planning areas
Sengkang, Bedok, Tampines19% of the blended underlying occupation families live across these three planning areas.
Residential concentration
Broadly distributed30% live across the top five planning areas in the weighted occupation blend.
Commute pattern
Mid-range commutesWeighted average commute 37.5 minutes. 33% take 46 minutes or more.
Local context & support
Market detail
Industry vacancy overlays use the latest published detailed cross-tab, which can lag the main labour monitor.
- Vacancy rate is 3.1% and was essentially flat versus last quarter.
- Hiring read: recruitment is running above resignation (1.5% vs 0.9%).
- Retrenchment was low at 1.5 per 1,000 employees.
- 67.7% of retrenched workers re-entered employment within 12 months.
- Employer pressure is moderate, based on 10 recent Singapore-relevant company signals.
Frequently asked questions
Will AI replace QA Engineer?
QA Engineer has an estimated AI Exposure Rank of 38/100 — higher than 38% of official occupations. It is a synthetic blend of 3 occupations, not a job-loss probability. Estimated AI exposure rank: 38/100 (High).
What is the AI exposure rank for QA Engineer?
QA Engineer has an estimated relative AI Exposure Rank of 38/100, rated High. This is a synthetic relative estimate blending 3 official occupations in Singapore, not a job-loss probability.
What occupations make up the QA Engineer estimate?
QA Engineer is estimated from 3 official occupations in Singapore: ICT quality assurance specialist (50%), Software developer (30%), ICT business process consultant/Business analyst (20%).