Principal AI Engineer

Location: LATAM - Remote

Type: Full-Time

We are seeking an experienced, hands-on Principal AI Engineer to drive the technical architecture and production engineering of artificial intelligence and machine learning solutions. Sitting at the intersection of software engineering, distributed systems, platform architecture, and ML engineering, you will serve as the technical owner for how AI/ML systems are designed, built, evaluated, and shipped to production.

This is a high-impact, 100% hands-on engineering and technical leadership position. You will move fluidly between writing production code, architecting multi-tenant AI services, designing MLOps and model evaluation pipelines, establishing AI governance, and guiding engineering teams.

• Location: Must be located in LATAM (Role is 100% Remote).
• Seniority & Track Record: 12–15+ years of software engineering experience, from Backend/Systems Architecture into applied Production ML Engineering.
• Education: Bachelor’s degree or higher in Computer Science, Software Engineering, or a related technical field.
• Hands-on Builder Mindset: Strongly motivated by coding, system design, and technical problem-solving.
• Production ML Engineering: Deep experience moving beyond LLM API consumption into true ML Engineering—model evaluation, prompt engineering at scale, vector search optimization, fine-tuning, and MLOps tooling.
• Software Architecture: Demonstrated track record designing distributed systems, asynchronous event-driven architectures, microservices, and multi-tenant platforms in Python, Go, or TypeScript.
• DevOps & Infrastructure: Solid, practical command of containerization (Docker), cloud infrastructure (AWS/GCP/Azure), and CI/CD pipelines needed to ship and support your own services.
• AI Security & Governance: Substantive experience with AI/LLM security risks (prompt injection, data boundary enforcement, model supply chain risks, threat modeling).
• Executive Communication: Exceptional verbal and written English skills. Proven ability to explain technical trade-offs, architecture decisions, and business impacts directly to senior stakeholders and PMs without jargon.

• Prior experience applying AI/ML within business consulting, advisory, professional services.
• Hands-on experience with multi-agent systems and agent orchestration frameworks (LangGraph, AutoGen, CrewAI, DSPy, MCP).
• Active contributions to open-source AI/ML projects, technical publications, or AI community initiatives.
• Experience defining AI compliance controls for SOC2, ISO 27001, or TISAX frameworks.

• Production ML & System Design: Design and build maintainable, scalable, and resilient production systems that integrate machine learning models, LLMs, vector databases, and agentic workflows into application architectures.
• Model Evaluation & MLOps: Establish robust model evaluation rubrics, observability pipelines, and benchmarking frameworks to monitor model performance, drift, latency, costs, and hallucination rates in production.
• AI Governance & Safety: Establish robust AI agent governance policies (permissions, code execution controls, system access, human-in-the-loop enforcement, and prompt security/data boundaries).
• Reusable Tooling & Scaffolding: Build reusable internal tooling, including AI scaffolding, monitoring systems, and data infrastructure designed for widespread developer adoption.
• Deployment & CI/CD: Define standardized deployment patterns using containerization, Infrastructure-as-Code (IaC), and reusable CI/CD pipelines to streamline service delivery.

• Engineering Standards: Codify software development standards (CI/CD, testing, delivery quality, async patterns) referenced as a baseline for new or re-platformed products.
• AI-Assisted Development: Champion AI-assisted development practices, test-driven development (TDD), and modern engineering workflows across the organization.
• Technical Mentorship: Mentor engineers and tech leads by example through code reviews, design docs, and architectural guidance.

• Product Inception Partner: Collaborate closely with Product Managers from product inception to translate business requirements into feasible, scalable technical architectures.
• Technical Authority: Act as the primary technical authority on AI/ML and software architecture, translating complex architectural choices, model trade-offs (e.g., RAG vs. Fine-Tuning, latency vs. accuracy), and risk topics into clear, actionable executive guidance.

About RYZ Labs

RYZ Labs is a startup studio built in 2021 by two lifelong entrepreneurs. The founders of RYZ have worked at some of the world's largest tech companies and some of the most iconic consumer brands. They have lived and worked in Argentina for many years and have decades of experience in Latam. What brought them together is the passion for the early phases of company creation and the idea of attracting the brightest talents in order to build industry-defining companies in a post-pandemic world.

Our teams are remote and distributed throughout the US and Latam. They use the latest cutting-edge technologies in cloud computing to create applications that are scalable and resilient. We aim to provide diverse product solutions for different industries, planning to build a large number of startups in the upcoming years.

At RYZ, you will find yourself working with autonomy and efficiency, owning every step of your development. We provide an environment of opportunities, learning, growth, expansion and challenging projects. You will deepen your experience while sharing and learning from a team of great professionals and specialists.

Our values and what to expect

• Customer First Mentality – every decision we make should be made through the lens of the customer.
• Bias for Action – urgency is critical, expect that the timeline to get something done is accelerated.
• Ownership – step up if you see an opportunity to help, even if not your core responsibility.
• Humility and Respect – be willing to learn, be vulnerable, and treat everyone that interacts with RYZ with respect.
• Frugality – being frugal and cost-conscious helps us do more with less.
• Deliver Impact – get things done in the most efficient way.
• Raise our Standards – always be looking to improve our processes, our team, our expectations. Status quo is not good enough and never should be.