AI Solutions Engineer (Staff)

Argentina·Buenos AiresRemoteFull Time - Contractlead

OtherAi Solutions Engineer

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Quick Summary

Overview

Remote, only for candidates in LATAM At Ryz Labs we are looking for an AI Solutions Engineer (Staff) to join one of our clients' teams. This is a first-of-its-kind role,

Technical Tools

OtherAi Solutions Engineer

Remote, only for candidates in LATAM

At Ryz Labs we are looking for an AI Solutions Engineer (Staff) to join one of our clients' teams. This is a first-of-its-kind role, sitting at the intersection of platform engineering, AI-assisted development, and business-facing technical advisory.

As AI-assisted development has become a core part of how teams across the business build internal tools, workflow applications, and operational software, a dedicated engineering function is needed to ensure that what gets built is scalable, secure, and maintainable. The AI Solutions Engineer will own the engineering layer that supports this capability — configuring and evolving the platform that underpins it, establishing the standards that govern how AI-generated applications are built and deployed, and serving as a technical advisor to non-technical stakeholders throughout the process.

This role requires someone who can operate at both the platform and the people layer: building tooling that enables teams to move faster and more independently, while also advising on risk, trade-offs, and technical feasibility in plain language. The right person has genuine fluency with modern AI development workflows, earned by actually building with these tools, alongside deep production experience in Elixir and AWS.

Responsibilities

~1 min read

→Own configuration, administration, and ongoing maintenance of our AI-powered application platform
→Collaborate with infrastructure engineers to shape the framework and standards that govern how AI-assisted applications are built, reviewed, and deployed.
→Design and build tooling that enables teams to develop and iterate on applications with greater independence and less engineering overhead
→Evaluate AI-generated code for security, scalability, and production readiness, and define code review standards specific to AI-assisted development workflows
→Serve as a technical advisor to non-technical stakeholders — helping them understand what is possible, where risk lives, and when engineering involvement is required
→Establish and promote best practices for AI-assisted development across the engineering organization
→Partner with the AI Solutions team and engineering leadership to define the long-term architecture of this platform as it scales

8+ years of experience building and shipping production-grade applications
Production experience in Elixir; ability to evaluate, refactor, and extend Elixir codebases and guide others doing the same
Experience with CI/CD tooling (GitHub Actions or similar) and infrastructure as code (Terraform, CloudFormation)
Deep working knowledge of modern AI development tools and LLM-assisted coding workflows (e.g., Claude, Cursor, Copilot, Lovable, or similar), with the technical depth to critically evaluate their output
Direct, hands-on experience building AI-powered applications — not just familiarity with the tools, but a track record of having shipped them
Experience in regulated environments or with applications subject to data sensitivity requirements (MNPI, PII, or similar)
Hands-on AWS experience, including deployment, infrastructure management, and cloud-native service patterns (Lambda, ECS/EKS, RDS, S3, SQS)
Experience building internal platforms or self-service developer tooling that reduces engineering toil and enables non-technical users
Ability to communicate clearly with non-technical stakeholders — translating technical constraints into plain language and advising business users on risk without requiring them to understand the underlying architecture
Strong ownership mindset: comfortable operating with ambiguity and defining the path forward with minimal direction