AI Business Partner

Role Overview

• Executive Problem Framing & Prioritization
• Partner with SBU and functional leadership to identify fundamental business problems with transformative AI potential.
• Frame AI opportunities with financial, strategic, and technical rigor, enabling confident investment decisions.
• Stack-rank AI initiatives based on value potential, feasibility, and execution risk.
• AI Solution Architecture
• Work directly with CIOs and technology leaders as a credible AI solution architect, not simply as a strategy or relationship lead, contributing to architectural decisions, trade-off analysis, and solution design.
• Pattern-match business problems to existing AI solutions, reusable frameworks, and prior implementations.
• Shape build vs. buy vs. adapt decisions with an enterprise-scale mindset.
• Product & Specification Leadership
• Apply strong product thinking to define AI use cases with execution-ready depth.
• Write clear specs, requirements, and acceptance criteria in direct partnership with engineering and data science teams.
• Evaluate solutions for user value, viability, and iteration path — not just strategic fit.
• POC & Early-Stage Execution
• Work at a product-builder level alongside engineering, SMEs, and operations to develop and iterate on POCs, prototypes, pilots, and early-stage production solutions.
• Practice AI-first development as standard.
• Spec-driven development and agentic tools like Cursor and Claude Code are operating procedure, not optional additions.
• Guide business units through the AI lifecycle from ideation to value realization.
• Portfolio & Cross-Functional Leadership
• Partner with the PMO and AI Enablement teams to manage a prioritized AI portfolio and track value realization.
• Communicate progress, risk, and impact to executive stakeholders.
• Champion adoption of enterprise AI frameworks and best practices across business and technology teams.

Requirements

• Demonstrated technical foundation with at least two of the following:
• Formal education in engineering, computer science, data science, or related field
• Professional training in AI/ML
• Hands-on experience building AI or data-intensive systems
• Proven experience working in an AI-first way, actively using modern agentic development tools.
• Strong product management or product engineering experience with the ability to move from executive narrative to detailed specs to shipped solutions.
• Experience partnering with engineering and data science teams as a technical peer.
• Financial and analytical acumen to assess value and execution risk.
• Executive presence with credibility at both C-suite and CIO/engineering leadership levels.

Benefits

• medical insurance
• vision insurance
• dental insurance
• well-being and behavioral health programs
• 401(k)
• company paid life insurance
• tuition reimbursement
• a minimum of 18 days of paid time off per year
• paid holidays