Finance Artificial Intelligence

H.J. Heinz Co. Australia Ltd Company

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Mexico City - Antara Tower A - 5th Floor - Local Office Until 10/4/2026 5+ years exp H-1B sponsor history First posted August 5, 2026 Last posted August 5, 2026
Job description

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.

About this role

Summary

Manage deployment, adoption, and governance of AI tools for finance in enterprise setting.

Job title

Finance Artificial Intelligence

Experience level

5+ years

Minimum experience

5+ years exp

Industry

food and beverage

Location requirements

On-site in Mexico City, no remote work allowed.

Salary

Not specified

Visa sponsorship

H-1B sponsor history

Management role

Yes

Skills & keywords

Required skills

data engineeringML deploymentPythonSnowflakedata governance

Preferred skills

MLOpschange managementmentorshipfinancial data

Specializations

AI deploymentML workflowsdata governanceenterprise softwareMLOps
Locations

Structured locations inferred from the posting.

Mexico City, CDMX, Mexico

On-site City