Sr AI Engineer (ML & Data)

Accountabilities: Design, build, and deploy AI agents and features end to end, from initial specifications through production. Deliver early iterations and continuously improve solutions based on feedback from real users. Collaborate with product, support, and engineering stakeholders to translate business challenges into clear technical requirements. Develop AI agents and machine learning features using large datasets and Databricks. Build and manage batch and streaming data pipelines to support AI-powered applications. Monitor production solutions, evaluate agent performance, manage costs, and troubleshoot failures. Promote best practices in agentic engineering to improve development speed, reliability, and team productivity. Use coding agents as primary development tools, defining tasks, reviewing generated outputs, validating results, and coordinating parallel workflows. Strengthen engineering processes through testing, CI, agent reviews, and reusable skills that prevent recurring issues. Requirements: Professional background in machine learning or AI engineering. Proven experience delivering AI agents or LLM-powered features to production, with real users actively relying on them. Hands-on experience with Databricks, including developing and managing batch and streaming data pipelines. Cloud experience with AWS and/or Azure. Experience using evaluations and data to determine when AI agents are ready for deployment and measure their effectiveness in production. Strong Python proficiency, with practical experience building solutions using LLM APIs and MCP. Familiarity with agent frameworks or SDKs, including the ability to identify when a framework is unnecessary. Established experience using coding agents as the primary approach to software development. Ability to work independently, gather requirements from non-engineering stakeholders, communicate clearly, and provide specific, honest answers. Advanced written and spoken English, as the role operates entirely in English. Availability to overlap with US Eastern business hours, approximately 9 AM–5 PM. Willingness to participate in hands-on technical interviews, including detailed discussions of solutions previously built and shipped. Nice to have: Experience owning deployment processes, including CI/CD, infrastructure as code (Terraform), and monitoring. Experience processing complex documents with LLMs, including OCR and data extraction. Familiarity with MLOps tools such as MLflow. Background in logistics, transportation, or compliance. Benefits: Monthly service fee paid in USD. 20 business days of paid agreed time off annually. Six local holidays. Caregiver time off. Fully remote work arrangement, with the flexibility to work from anywhere in Latin America. Dynamic and entrepreneurial work environment.