tech
Mobile Engineer: modeled AI cost and task mix
Builds and ships the iOS / Android app: UI, native SDK integration, performance, crash triage, and store releases. Owns the on-device experience end to end.
This page uses a representative geography and experience level. Build your own Wagecard to use your actual task mix, hours, location, experience, and optional salary.
- Operational AI cost
- Market pay (p50)
- Four task classes
- Qualitative confidence
- Documented methodology
Operational AI cost
Modeled AI running cost includes tokens, human review, retries, error cost, integration, and orchestration.
Market pay (US Tier 2, mid-career)
Market pay percentiles: p25 $106,684, p75 $151,671, p90 $179,949.
Economic substitution exposure
Lower scores mean a person is more reliable or cost-effective for more of the task time. Augmentation territory.
Task mix
Four task classes
Hours-weighted share of this role's tasks
Task details
How each task was classified
For each task, see AI capability, reliability, error cost, and where a person remains more reliable or cost-effective.
| Task | Capability | Reliability | Error cost | Human-advantage |
|---|---|---|---|---|
| Build UI screens and features | 76 | 68 | 3/5 | 30/100 |
| Integrate native SDKs and APIs | 64 | 56 | 3/5 | 42/100 |
| Debug device-specific crashes | 45 | 42 | 4/5 | 65/100 |
| Optimize performance and battery | 48 | 45 | 3/5 | 60/100 |
| Manage app-store releases | 52 | 50 | 4/5 | 55/100 |
| Architect app module boundaries | 44 | 40 | 5/5 | 75/100 |
Representative US Tier 2, mid-career example using capability matrix v1 and model v1-mvp. See the documented methodology at /methodology.
Build a Wagecard for your Mobile Engineer task mix
Use your actual tasks, hours, location, experience, and optional salary. Your Wagecard shows modeled AI running cost, market pay, the four task classes, and qualitative confidence on the core estimates.