Hire senior Forward Deployed Engineers from Latin America

Hire Forward Deployed Engineers

Engineers who embed with your team or your customer, find the highest-value AI use case, and ship it in weeks — half builder, half consultant, fluent in both code and stakeholders. Onboarded in one week.

About the role

The Forward Deployed Engineer role consists of embedding where the problem lives — inside your customer's team or your own business unit — finding the highest-value AI use case, and shipping it on real systems in weeks. Half builder, half consultant, comfortable in a workshop with executives at 10am and in the codebase at 2pm. Palantir invented the title; every AI company selling to enterprises now hires for it.

Monthly rate

$6,000–$9,000/mo

All-in: contract, benefits, equipment, IP

Experience

10+ years engineering

client-facing delivery

Location

Latin America

Argentina · Colombia · Mexico

Timezone

Full US overlap

Fluent English, onboarded in one week

Core stack

Claude APIOpenAIRAGPython / TypeScriptRapid prototypingSystems integration

AI tools, daily

Claude CodeCursorAnthropic Console

Verticals seen

Enterprise agenticFintechSaaSLegal & compliance

What they own — and what they don't

What they own

  • Embed with a customer or business unit and run discovery on their actual workflows and data
  • Ship working software against the customer's systems in weekly increments — demos on real data, not slideware
  • Adapt your platform or AI product to the messy specifics of each deployment
  • Run stakeholder demos, workshops, and technical sessions in fluent English, US hours
  • Feed what the field teaches back into your product roadmap

What they don't — and who does instead

  • Build your core platform — that's your product engineering team's job
  • Own the commercial relationship or quota — they make the account technically successful, sales closes it
  • Design company-wide AI strategy — that's an AI Solutions Architect
  • Operate as a long-term augmented team member on one internal codebase — that's classic staff augmentation

Who hires this role, and for what

  • AI companies selling into enterprises. The product demos well, but every enterprise deal needs someone to make it work on that customer's data, systems, and politics. FDEs are how AI products actually land.

  • Platform companies with long time-to-value. Customers churn in onboarding because integration is hard. An embedded FDE compresses months of 'getting value' into weeks.

  • Enterprises running internal AI transformation. Instead of a consultancy that leaves a deck, they embed an FDE in one business unit to ship a working use case and leave running software.

  1. 01

    Enterprise deployment of an AI product. Landing your product inside a large customer — integration, data mapping, security review, and the first live workflow.

  2. 02

    Discovery-to-demo sprints. Two to four weeks from stakeholder interviews to a working demo on the customer's real data — the artifact that closes or expands the deal.

  3. 03

    Lighthouse customer success. Making the first big-logo deployment undeniably successful, so the case study writes itself.

  4. 04

    Internal use-case delivery. Embedded in one business unit, shipping an AI workflow end to end while training the local team to run it.

Work our engineers at this role have shipped

  • Embedded engagement turning a Fortune 500 support flow into a voice-first conversational agent
  • Two-week discovery-to-demo cycle that landed an enterprise AI rollout for a platform client
  • On-site style embedded delivery (US timezone) shipping weekly increments against a client's internal systems

Do you actually need a Forward Deployed Engineer?

You do, if:

  • Enterprise deals stall between signed contract and live deployment
  • Your product needs per-customer engineering and your core team is drowning in it
  • Time-to-value for new customers is measured in months and churn shows it
  • You need someone who can hold the room with a VP and then go implement what was agreed

You probably don't, if:

  • The work is on one internal codebase with your own team — regular staff augmentation is cheaper and fits better
  • You need product strategy across many accounts, not delivery inside one — that's a Solutions Architect or AI PM
  • There's no customer or stakeholder interface in the role — then you just need a strong senior engineer

Not sure which role fits? Tell us the problem instead of the title — we'll tell you what we'd actually staff, even if it's not this. If it is this: discovery call today, matched profiles in 48 hours, onboarded in a week.

Hire a Senior Forward Deployed Engineer

Common questions

  • They sit at the edge between your product and a real customer problem. Instead of building the platform, they build on it — embedded with the account, shipping working software against the customer's actual data and systems, feeding what they learn back to your product team. The role Palantir made famous and every AI company now hires for.

Ready to talk?

Drop us a line

Or email directly: sales@greelow.com

Book a call