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

• 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.

Backend Software Engineer – AI Training Projects

• Provide technical direction for dLocal’s data and analytics architecture
• Shape a scalable, governed, and highly consumable data ecosystem across Data & AI and engineering
• Connect domain-owned data products, real-time platforms, analytical workloads, machine-learning use cases, and business-facing data consumption
• Define and evolve enterprise data architectures across batch, streaming, lakehouse, warehouse, and operational use cases
• Review and advise architects on data aspects of RFCs
• Lead adoption of data-mesh principles, including domain ownership, data as a product, federated governance, self-serve platforms, discoverability, quality, and data-product SLAs
• Establish reference architectures and engineering standards for data products, pipelines, ingestion, storage, processing, orchestration, observability, lineage, security, and access management
• Design and govern streaming architectures using Kafka, Kinesis, Flink, Spark Structured Streaming, and Databricks
• Define event-processing patterns including schemas, data contracts, event-time processing, late-event handling, idempotency, deduplication, replay, reprocessing, dead-letter flows, and freshness SLAs
• Shape semantic layers and enterprise ontologies across domains
• Guide cloud data platforms and lakehouse capabilities across AWS and GCP
• Provide architectural direction for MLOps and feature-platform capabilities
• Lead or contribute to architecture RFCs, technical decisions, design reviews, migration plans, and implementation roadmaps
• Partner with domain teams on ownership, data-product responsibilities, operational handover, quality accountability, access approval, and cross-domain consumption
• Define controls for data quality, observability, privacy, security, resilience, cost management, and production readiness
• Resolve critical architectural issues across teams and ensure decisions reach implementation and operation
• Mentor data engineers, platform teams, data scientists, MLOps engineers, BI teams, and engineering leaders
• Communicate architectural vision while validating designs in production

AI Engineer jobs in Uruguay

Unity Developer – AI Forward

Backend Software Engineer – AI Training Projects

Data-AI Architect