Hire senior AI Solutions Architects from Latin America

Hire AI Solutions Architects

The person who decides where AI actually belongs in your stack — use-case triage, model selection, build vs buy, integration with the systems you already run, and the security review before anything ships. Onboarded in one week.

About the role

The AI Solutions Architect role consists of deciding where AI actually belongs in your company — and, just as important, where it doesn't: triaging use cases, picking models, calling build-vs-buy, and designing how AI integrates with the systems you already run. It's the role that stops the two most expensive failure modes in enterprise AI: building the wrong thing well, and buying six tools that don't talk to each other.

Monthly rate

$6,500–$9,500/mo

All-in: contract, benefits, equipment, IP

Experience

12+ years engineering

3+ in AI delivery

Location

Latin America

Argentina · Colombia · Mexico

Timezone

Full US overlap

Fluent English, onboarded in one week

Core stack

Claude APIOpenAIRAGAWS / GCPSystems integrationEvals & cost modeling

AI tools, daily

Claude CodeCursorAnthropic Console

Verticals seen

FintechHealthcareEnterprise agenticSaaS

What they own — and what they don't

What they own

  • Triage AI use cases by value, feasibility, and risk — and kill the ones that won't pay
  • Design the reference architecture: model selection, data flows, integration points with existing systems
  • Make build-vs-buy calls with cost and latency numbers attached, not vendor slides
  • Own the security and compliance surface: what data leaves the perimeter, provider agreements, access boundaries
  • Translate between the board's 'we need an AI strategy' and engineering's concrete next quarter

What they don't — and who does instead

  • Write the production features themselves day to day — AI Engineers build to the architecture
  • Go deep on multi-agent orchestration internals — that's the AI Agent Architect's lane
  • Adversarially test what got built — that's AI Security & Red Teaming
  • Own the product roadmap and user experience of AI features — that's an AI Product Manager

Who hires this role, and for what

  • Mid-market companies with AI mandate, no AI plan. The CEO promised AI to the board. The Solutions Architect turns the mandate into three sequenced use cases with architecture, budget, and a delivery path.

  • Enterprises drowning in vendor pitches. Every tool now claims AI. They need someone technical and neutral who can score options against their actual stack and data reality.

  • CTOs about to make a big AI bet. Before committing headcount and budget to a direction, they want one senior person to pressure-test the architecture across systems, cost, and compliance.

  1. 01

    AI roadmap with architecture. From fifty ideas to three funded use cases, each with a reference design, cost model, and integration plan.

  2. 02

    Build-vs-buy decisions. Evaluating vendors against building on foundation models directly — with real token math, not intuition.

  3. 03

    Legacy-system AI integration. Getting AI value out of the ERP, CRM, and data warehouse you already have, without a two-year replatform first.

  4. 04

    LLM cost and model rationalization. Consolidating scattered AI experiments onto a sane architecture — right model per task, one gateway, one bill someone owns.

Work our engineers at this role have shipped

  • AI adoption roadmap and reference architecture for a mid-market SaaS — three use cases shipped in the first quarter
  • RAG pipeline over 100K internal docs for a mid-market SaaS
  • Model-selection and cost-modeling exercise that cut a client's LLM spend without losing output quality

Do you actually need an AI Solutions Architect?

You do, if:

  • You have AI budget and pressure to use it, but no prioritized list of what to build
  • Multiple teams are running uncoordinated AI experiments with no shared architecture
  • A vendor decision above a six-figure commitment is on the table and nobody technical is neutral
  • Compliance or security keeps blocking AI initiatives because nobody mapped the data flows

You probably don't, if:

  • The use case is already decided and scoped — go straight to an AI Engineer to build it
  • Your whole AI surface is one feature in one product — a senior AI Engineer can own that architecture
  • What you're missing is delivery speed, not direction — that's staffing, not strategy

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 AI Solutions Architect

Common questions

  • The Solutions Architect works across your whole stack: which use cases are worth doing, which model fits each one, build vs buy, and how AI integrates with the systems you already run. The Agent Architect goes deep on one class of system — multi-agent orchestration. If you're deciding what to do with AI, start with a Solutions Architect. If you've decided and it's agents, get an Agent Architect.

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