We source, screen and place a remote AI automation specialist directly on your team. They build production workflows in n8n, Make and Zapier, work US hours, and come with a 12-month replacement guarantee. Talent from $10 per hour.
Most teams that try to hire an AI automation specialist end up with someone who can demo a ChatGPT integration and not much more. The workflow runs fine on a clean test record, then fails the first time a lead arrives with a missing field, a webhook times out, or the model returns malformed JSON. Nobody notices until the CRM is a week behind.
A real AI automation specialist designs for failure. They add error routes, retries and logging, validate every model output against a schema, and document each scenario so your ops team can read it. RevHires places remote specialists who have already proven that on a live build test, and they work your hours, so problems get fixed the day they surface.
An AI automation specialist, sometimes called an AI workflow automation specialist, no-code automation engineer or AI operations specialist, connects your business systems and inserts large language models where judgment used to require a person. They map a manual process, build it in a platform like n8n, Make or Zapier, call the OpenAI or Anthropic API for steps like classification, extraction and drafting, and route results into your CRM, help desk or database. The role sits between operations and engineering: less code than an AI engineer, far more rigor than a power user.
Interviews the people doing the work today, documents every step, input and exception, and flags which steps suit fixed rules, which need an LLM and which should stay human. You get a written scope with estimated hours saved per week before any build starts.
Builds scenarios in n8n, Make or Zapier that trigger on form fills, emails, webhooks or schedules, then branch, loop and aggregate data across apps. Uses routers, iterators and sub-workflows so one build handles the edge cases your team currently fixes by hand.
Writes prompts for the OpenAI and Anthropic APIs that classify tickets, extract fields from PDFs or score leads, and forces structured JSON output. Validates every response against a schema and routes anything that fails to a retry or a human review queue.
Keeps HubSpot, Salesforce, GoHighLevel, Zendesk or Intercom in sync with the rest of your stack. Deduplicates contacts, maps custom fields, enriches records and writes AI-generated summaries back to the right object so reps see context without opening five tabs.
Adds error routes, retries with backoff, and alerts to Slack or email when a run fails. Logs inputs, outputs and token usage so failed runs can be replayed. Reviews execution history every week and fixes the root cause instead of rerunning broken jobs.
Parses invoices, applications, contracts and inbound emails with OCR plus an LLM, extracts the fields you care about, and files them in Google Drive, Airtable or your database. Sets confidence thresholds so uncertain extractions go to a person, not straight into your books.
Picks the right model size for each step, batches calls, caches repeated lookups and watches operation counts in Make and task counts in Zapier. Keeps your automation bill and API spend predictable as volume grows, instead of discovering the overage at month end.
Names every module clearly, writes a runbook per workflow covering triggers, dependencies, credential owners and known failure modes, and records short Loom walkthroughs. When someone on your team opens a scenario six months later, they understand it in minutes.
Every profile includes a voice clip, enterprise background, English level and a scored role play.
Every AI automation specialist candidate completes a timed live build: take a messy inbound lead webhook, enrich it, classify intent with an LLM, enforce JSON output, write it to a CRM and alert Slack when anything fails. We grade error handling and documentation, not just whether it runs. Then comes a technical interview on a past scenario they built, a written runbook sample to test English, and reference checks before you see a shortlist.
The US figure is Indeed's national average base salary for automation specialists, a broad title that includes some non-AI roles, so treat it as a conservative floor. We add 30% for payroll tax and benefits and leave out recruiting fees, equipment and software. Through RevHires, a full-time hire in this role typically earns $10 to $25 per hour. The RevHires figure uses the top of that range, $25 per hour at 40 hours, paid direct to your hire or through RevHires, plus one flat placement fee. Want the team managed for you? Done-for-you pricing is covered on your strategy call.
Role scorecard, stack, salary band and must-haves.
Targeted search across Latin America, South Africa and Egypt.
Language, enterprise background and a role test.
Vetted finalists with recorded intros.
Your interviews, your offer, 12-month guarantee.
One flat placement fee, due only when your hire accepts. 12-month replacement guarantee. Pay your hire direct, or through RevHires and we handle payroll.
Through RevHires, a full-time AI automation specialist typically earns $10 to $25 per hour, about $1,730 to $4,330 per month, paid direct to your hire or through RevHires. You pay one flat placement fee, and only when you hire. Want the team managed for you? Done-for-you pricing is covered on your strategy call.
After a discovery call where we confirm your platforms, use cases and seniority level, we run a custom search and deliver 2 to 3 screened candidates within 48 to 72 hours. You only interview people who have already passed our live build test. After that, the timeline mostly depends on your interview schedule and how quickly you make an offer.
We screen for near-native English and for experience automating processes at companies that sell into the US, UK, Canada or Australia. Many candidates come from enterprises like Vodafone, Microsoft or Amazon. They write specs and runbooks your ops leads can follow, and they ask clarifying questions about your business rules before building instead of guessing and rebuilding later.
Your specialist works US business hours, so they join standups, debug a failing scenario while it is happening, and answer Slack the same day. Depending on the market you hire from, your hire is 0 to 10 hours from US time zones, and every candidate we place agrees to your schedule up front. Overnight runs are covered by the alerting and retries they build into each workflow.
With talent placement, the specialist joins your team and reports to your manager, like any domestic hire. We provide role-specific onboarding before day one. We recommend a 30, 60 and 90 day plan with clear metrics such as workflows shipped, hours saved and failed run rate. If you would rather have a team RevHires manages for you, ask about our managed model on your strategy call.
Every engagement includes an NDA and documented data handling protocols, and RevHires signs BAAs for healthcare clients. We recommend your specialist works inside your own n8n, Make or Zapier workspace with role-based access, keeps scoped API keys in the platform's credential store, and never pastes customer data into personal AI accounts. You own every workflow, prompt and credential they create.
Every placement includes a 12-month replacement guarantee. If the specialist is not working out within that window, tell us and we run a replacement search under your 12-month guarantee. Because we screen with a live build test, mismatches usually come down to scope or seniority, which is why we pin both down carefully on the discovery call.
See the shortlist, hear the voice clips, and get the right hire in front of your buyers fast.