Senior Manager, AI & Machine Learning Engineering

What you'll do

• Lead the design and execution of the AI/ML architecture and technical strategy for the D-Fi platform.
• Manage a global engineering team in Buenos Aires to deliver production-grade AI, data foundations, and software workflows.
• Translate complex finance business requirements into scoped, actionable technical roadmaps for stakeholders and leadership.
• Oversee the end-to-end development of LLM capabilities, including RAG pipelines, prompt engineering, and vector database integration.
• Enforce data governance by designing role-based access controls at the data model level.
• Establish engineering standards for code review, testing, model evaluation, and release management across distributed teams.
• Make critical "build vs. integrate" decisions regarding custom capabilities versus existing enterprise systems like SAP and Cognos.
• Perform hands-on technical tasks including code reviews, troubleshooting, and evaluating architectural trade-offs.

What we're looking for

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Advanced degree in a technical field (preferred).
• 10+ years of software and/or ML engineering leadership experience with a track record of owning end-to-end architecture for complex systems.
• Demonstrated experience architecting and shipping production LLM/AI applications including RAG pipelines, prompt engineering, and retrieval design at scale.
• Working knowledge of LLM orchestration frameworks (e.g., LangChain, LlamaIndex) and vector databases or retrieval stores.
• Strong data modeling background, ideally including semantic and governed data layers.
• Ability to read, write, and review Python code.
• Familiarity with MLOps practices, modern web/full-stack languages, and experience leading distributed, cross-timezone engineering teams.
• Experience building internal tools for finance organizations (preferred).
• Exposure to ERP/EPM platforms such as SAP, Oracle EPM, or Cognos, and experience integrating applications against enterprise system APIs (preferred).
• Experience evaluating third-party or consulting-delivered engineering work (preferred).