Sobre esta vaga de Principal AI Engineer na Ryz Labs
Ryz Labs · Híbrido · Argentina
Location: LATAM - Remote
Type: Full-Time
About the Opportunity
We are seeking an experienced and visionary Principal AI Engineer to drive the technical evolution of artificial intelligence and machine learning solutions across our global business portfolio. Sitting at the intersection of software engineering, data science, platform architecture, and AI governance, you will serve as the technical owner for how AI/ML engineering is designed, built, governed, and deployed.
This is a high-impact, hands-on engineering and technical leadership position. You will move fluidly between writing production code, architecting multi-tenant AI services, building internal developer tooling, establishing AI governance, and mentoring engineering teams. Your success will be measured by sustainable, scalable patterns that empower teams and shape the future of our digital capabilities.
What You Will Do
• AI Productization & Platform EngineeringDesign and own the playbook for AI productization and governance, defining service patterns, security standards, evaluation rubrics, and production-readiness criteria.
• Build reusable internal tooling, including AI scaffolding, monitoring systems, and data infrastructure designed for widespread adoption.
• Establish robust AI agent governance policies (permissions, code execution controls, system access, human-in-the-loop enforcement).
• Partner with Security, Legal, and Compliance teams to define SOC2/ISO-aligned AI controls, vendor requirements, and data classification policies.
• Define standardized deployment patterns using containerization, Infrastructure-as-Code (IaC), and reusable CI/CD pipelines.
Developer Experience & Engineering Excellence
• Champion AI-assisted development practices, test-driven development (TDD), and modern software engineering standards across the organization.
• Codify engineering baselines (CI/CD, DevOps, testing, delivery quality) for new and re-platformed products.
• Mentor engineers and tech leads, driving measurable improvements in design quality, consistency, and production rigor.
Cross-Functional Leadership & Strategy
• Act as the primary technical authority on AI/ML, platform architecture, and modern engineering practices.
• Bridge the gap between technical and non-technical stakeholders, translating complex architectural decisions, AI risk topics, and platform trade-offs into actionable executive guidance.
What You Bring (Required Skills & Experience)
• Experience: 15+ years of experience in software engineering, data science, or a closely related technical field.
• Education: Bachelor’s degree or higher in Computer Science, Engineering, or a related field.
• AI/ML & Cloud: Deep expertise in the Python ecosystem and AI/ML frameworks, with proven experience deploying models to public cloud infrastructure.
• Architecture: Demonstrated track record designing and operating multi-tenant AI services, LLM integrations, and microservices architectures in production.
• DevOps & Infrastructure: Strong hands-on command of containerization (Docker), Infrastructure-as-Code (Terraform), and modern CI/CD practices.
• AI Security & Governance: Substantive experience with AI/LLM security risks (prompt injection, data boundary enforcement, model supply chain risks, threat modeling).
• Communication: Exceptional written and verbal English skills, with the ability to articulate complex technical ideas to diverse audiences and senior stakeholders.
• Mentorship & Culture: Passion for coaching, developing engineers, and advocating for engineering best practices.
• Workplace Flexibility: Willingness to work in a hybrid environment (office/remote) and flexibility to accommodate international client/project needs as required.
Nice-to-Have Qualifications
• Prior experience applying AI/ML within business consulting, advisory, or professional services environments.
• Hands-on experience with emerging AI integration protocols and gateway design patterns.
• Active contributions to open-source AI/ML projects, publications, or technical communities.
• Proficiency in additional programming languages (e.g., Go, TypeScript).
• Advanced certifications in Cloud, AI/ML, or Security (AWS, GCP, Azure ML, CISSP, etc.).
• Experience with compliance frameworks such as SOC2, ISO 27001, or TISAX.
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