Finance Artificial Intelligence

Job Description What’s on the menu? Own the deployment pipeline for Finance AI agents and tools — taking validated, production-ready components from the Infrastructure & Agents team and deploying them reliably to Finance business users across all pillars Build and own the Finance AI enablement layer — user guides, onboarding materials, training content, and the documentation that lets Finance teams use AI tools without requiring the Architecture team in the room Own the Finance AI intake and release process — manage the queue of deployment requests from domain pillars, sequence releases, and coordinate with the Infrastructure & Agents Manager on readiness gates Build and maintain the Finance AI knowledge base — architecture decision records, prompt libraries, agent catalog, and the living documentation of what is deployed, where, and at what version Track and report adoption metrics across deployed Finance AI tools — usage, active users, error rates, and escalations — and feed that signal back to the Architecture Lead and domain pillar teams Support change management for Finance teams adopting AI tools — work with domain pillar leads to identify adoption blockers and build targeted interventions that are not just more training decks Manage and develop one Senior Analyst — set delivery standards, run reviews, and build someone who can own deployment tracks independently Coordinate with IT, Information Security, and Internal Audit on deployment governance — access controls, data classification, and the change management artifacts auditors will ask for Recipe for Success — apply now if this sounds like you! I have +5 years of experience in data engineering, analytics, or technical program management — with at least 1–2 years deploying or scaling AI/ML or analytics tools to business users I am technical enough to understand what I am deploying — I can read Snowflake pipelines, Python code, and agent configurations — even if I am not the primary builder I have experience managing deployment pipelines, release processes, or MLOps workflows for data or AI products in an enterprise environment I know how to drive adoption of technical tools with non-technical users — I have built enablement content that people actually use, not just documentation that gets ignored I understand data governance, access controls, and the audit documentation requirements of deploying AI in a SOX-regulated finance environment I have managed or mentored at least one person — I develop people through the work, not through separate development conversations I translate between technical teams and finance business users without losing meaning in either direction I have a Bachelor’s degree in Computer Science, Engineering, Finance, or a related field Location(s) Mexico City - Antara Tower A - 5th Floor - Local Office Kraft Heinz is an Equal Opportunity Employer – Underrepresented Ethnic Minority Groups/Women/Veterans/Individuals with Disabilities/Sexual Orientation/Gender Identity and other protected classes .