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)

Kraft Heinz is an Equal Opportunity Employer – Underrepresented Ethnic MinorityGroups/Women/Veterans/Individuals with Disabilities/Sexual Orientation/Gender Identity and other protected classes.