AI Platform Engineer

About the Role

Serves as the technical gatekeeper for AI tools built by non-developers and aids in the builds and deployment of AI solutions across the enterprise, specifically the CFO organization. Ensures that when a business user builds something with AI, it's safe, accurate, and operates within the established governance guidelines.

Key Responsibilities

• Review AI solutions built by non-developers against best-practice engineering standards and the team's governance framework before they go into production.
• Champion reusable architecture patterns and templates so solutions can be redeployed across all BUs rather than rebuilt each time.
• Assess citizen-developer builds for data lineage, model accuracy thresholds, human-in-the-loop safeguards, and audit trail compliance, then flag and lead to remediate gaps.
• Aid to implement automated output validation, drift detection, and exception escalation for solutions post-launch.
• Track token/API usage and cost at the solution and BU level; support monthly usage reporting to CFO leadership.
• Design, build, and deploy AI/LLM-integrated solutions for FP&A, accounting, audit, and reporting workflows; maintain all code in Git with version control and peer review.
• Partner with the FP&A AI Sr. Analyst on requirements, the AI Governance lead on control design, and enterprise IT/architecture on alignment.

Requirements & Tech Stack

Required Skills: Technical

• Python (or equivalent) for automation and data pipeline work.
• Cloud Platform Experience (Azure/AWS Preferred).
• Hands-on experience integrating LLM APIs (OpenAI, Anthropic, Azure OpenAI).
• Git-based version control, structured code review, and change management practices.
• SQL and ETL/data pipeline experience.
• Working familiarity with low-code/RPA platforms (Power Platform, UiPath, Copilot Studio), with enough depth to competently review, not necessarily build in them.
• Understanding of AI governance concepts: model validation, drift detection, data lineage, audit trails.

Required Skills: Domain & Communication

• Able to explain technical risk in plain language to non-technical finance staff whose builds are under review.
• Working knowledge of finance processes sufficient to judge business context and materiality of a given AI build.
• Comfortable working across business units with varying technical maturity.

Nice to Have

• Finance/accounting background or FP&A exposure.
• Experience standing up a citizen-developer governance program or AI Center of Excellence.
• SOX/internal controls familiarity.