Nearshore Automation Engineer for AI Operations teams
Builds the integrations and RPA that remove manual steps across CRM, ERP, monitoring and field tools.
A nearshore automation engineer is a trained, English-fluent professional based in Latin America who works U.S. hours inside your tools. Kurios City recruits, trains and deploys them in about 21 days, at 30–60% lower cost than a U.S.-based hire — the range published for LatAm back-office operations, with free replacement if the person doesn't perform.
What this role owns
- Integration design and build
- RPA for repetitive back-office tasks
- API connections and webhooks
- Error handling and logs
- Documentation and handover
Stack we train on
Cost comparison
- Salary$140,400
- Mandatory benefits & payroll taxes$37,257
- Social Security + Medicare, FUTA/SUTA, workers' comp, health insurance, 401(k), PTO
- Tools, management & recruiting$56,343
- AI licenceYou pay it
- If they don't work outYou start over
- One monthly fee$4,600
- Mandatory benefits & payroll taxes$0
- Handled in-country. None of it lands on your payroll.
- Recruiting, training, managementIncluded
- Claude or Codex licenceIncluded
- If they don't work outFree replacement
Example figures for a Automation Engineer. The U.S. side is fully loaded — what the role actually costs your company, not the salary line. Your real numbers come out of the first call.
| U.S. hire | Kurios nearshore | |
|---|---|---|
| Monthly cost | USD 16,000–23,000 | USD 4,000–5,200 |
| Time to fill | 45–90 days | 21 days |
| Training on your stack | Your team's time | Included |
| Replacement | New search | Free |
| Time-zone overlap | Full | Full (UTC−5 / −6) |
Ranges are indicative. Final figures are scoped per market, role and seniority.
What the first 90 days look like
Week 1–3
Reads your existing integrations and finds what is already broken but silently failing. There is usually at least one sync that stopped working months ago.
Week 4–8
Builds the first production integration with error handling, logging and alerting. Not a Zap that works on the happy path.
Month 3+
Owns integration reliability as a number — failed runs, mean time to detection, mean time to fix.
How to tell a good automation engineer from a cheap one
Distinguish between someone who can wire up no-code tools and someone who can write and maintain code. Both are legitimate hires at different prices. If your workflows fit Zapier or Make, do not pay for an engineer. If you need a real integration against an inverter monitoring API with retry logic and rate-limit handling, no-code will fail and you should hire accordingly. Ask which category they are; honest candidates answer directly.
How this role is measured
Mean time to detection. Integrations do not fail loudly by default. How long a broken sync runs before anyone notices is the difference between an annoyance and a data problem.
| What we track | Why it is the right number |
|---|---|
| Failed runs per week | With cause, not just a count |
| Mean time to detection | Minutes, not the next month's report |
| Mean time to repair | After detection |
| Integrations without a manual fallback | Should be zero |
These are the numbers we report back to you, not internal vanity metrics. If one of them stops moving, that is the conversation to have in the weekly check-in.
Available now
No profile available right now — request the role and Kurios sources it in 7–10 days.
Frequently asked
How do we know an integration is still working six months later?
Because it alerts when it produces nothing, not only when it throws an error. Silent failure is the normal way integrations die: the job runs, returns zero rows, and reports success for a month. Expected-volume checks are part of every build for that reason.
Do they work with our existing developers?
Yes, and they should be reviewed by them. This role is most effective when it handles the integration and workflow layer so your product developers stay on the product. Code review conventions are set by your team, not ours.
What if our systems have no API?
Then the honest options are file-based exchange, a scraping layer you accept will be brittle, or changing the system. We will lay out the trade-offs rather than promising an elegant integration that does not exist.