AI Engineer

• Build and maintain Unity (C#) field applications for sketching, configuring, and publishing pipe, duct, and other MEP work from jobsites
• Write production Unity code covering scene and prefab architecture, component lifecycle, input handling, UI, performance, and editor/runtime separation
• Own client-to-cloud integration, login, publishing, data synchronization, fidelity, and error handling between the Unity client and Stratus services
• Build and maintain automated Unity tests using NUnit, PlayMode integration tests, and EditMode unit tests
• Ship customer-facing enhancements across backend services, APIs, data, and web front end
• Design and build services and APIs connecting the web platform and cloud data
• Investigate and fix customer-reported bugs across client, service, and data layers
• Implement unit, integration, and end-to-end automated testing
• Contribute to monolith decomposition and modernization
• Use AI-assisted development tools and validate AI-generated changes with tests and engineering judgment
• Collaborate with product managers, designers, and customer-facing teams to define, design, scope, and ship features
• Coordinate deployments and incident response
• Advocate for incremental delivery
• Share knowledge through code reviews and pragmatic best practices

Unity Developer – AI Forward

• Desarrollar y mantener funcionalidades de producto sobre modelos fundacionales bajo el modelo Mission Pair
• Trabajar junto al Engineering Manager y Product Engineer
• Utilizar agentes de IA para llevar features y bugs end-to-end hasta producción
• Desarrollar features y resolver bugs asignados por el Engineering Manager
• Trabajar en par con un Product Engineer para traducir contexto de negocio en implementación técnica y entregar incrementos funcionales
• Comunicar proactivamente avances, riesgos y bloqueos
• Integrar nuevas features en pipelines de IA existentes, incluyendo RAG, prompt chains y servicios de modelo
• Ejecutar suites de evaluaciones y actuar sobre sus resultados antes de abrir Pull Requests
• Revisar y validar el output de agentes de IA antes de integrarlo
• Escribir tests unitarios y de integración, incluyendo cobertura del código generado por IA
• Participar en code reviews
• Documentar decisiones técnicas y patrones de implementación
• Participar en la demo semanal
• Usar agentes de IA para construir features end-to-end, analizar logs y stack traces, proponer fixes y generar documentación técnica
• Responder por el código generado por agentes como si fuera propio
• Mantener las métricas Core Web Vitals, DORA y System Health sin degradación

AI Engineer – Proyectos Core

• Design, build, and deploy production-grade data pipelines, analytics engines, and Generative AI/LLM applications using Databricks, Spark, Python/PySpark, and modern cloud ecosystems
• Serve as the primary technical leader on strategic enterprise client engagements
• Partner with C-level executives, VP/Directors of Data, and engineering teams to translate business challenges into technical solutions
• Lead complex legacy platform migrations onto the Databricks Lakehouse architecture
• Guide enterprise customers in adopting GenAI solutions, RAG architectures, model fine-tuning, and MLflow/Databricks Mosaic AI integrations
• Identify high-value technical use cases across client business units, expand Databricks platform usage, and drive measurable client ROI
• Mentor junior Solution Engineers, Architects, and Consultants
• Contribute to internal RevStar code libraries, reusable accelerators, and technical delivery best practices

Forward Deployed Engineer, AI/ML

• Create realistic, challenging coding tasks involving feature implementation and software bug fixes.
• Design tasks that reflect real-world backend engineering scenarios.
• Develop deterministic verifiers that accept reasonable valid solutions and reject incorrect outputs.
• Work with backend technologies such as Java, Node.js, Go, Rust, TypeScript, Python, C++, or similar languages.
• Evaluate code for correctness, reliability, maintainability, and performance.
• Incorporate automated testing and clear validation criteria into coding tasks.
• Identify and account for edge cases, performance bottlenecks, and potential implementation errors.
• Apply secure coding principles and cybersecurity considerations where relevant.
• Refine tasks and verification logic based on project requirements and quality standards.

AI Engineer jobs in Chile

Unity Developer – AI Forward

AI Engineer – Proyectos Core

Forward Deployed Engineer, AI/ML

Backend Software Engineer – AI Training Projects