Location: LATAM - Remote

Type: Full-Time

About The Opportunity

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.

What You Will Do

AI Productization, ML Engineering & Platform Architecture

- 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

Developer Experience & Engineering Excellence

- 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 Collaboration & Executive Communication

- 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

What You Bring (Required Skills & Experience)

- 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

Nice-to-Have Qualifications

- 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

📌 Principal AI Engineer (Argentina)
🏢 Ryz Labs
📍 Argentina