AI Business Partner

The AI Business Partner (AIBP) is a technical, AI-native product operator embedded with senior business leaders. This role identifies high-value business problems, architects AI solutions, and drives them from concept through early production.

This is not a coordination or translation role. The AIBP operates comfortably across the executive table, solution architecture, and hands-on early-stage build work, requiring executive presence, product judgment, and real technical depth in AI-first development.

AI is core to how top candidates work, already practicing spec-driven development, using agentic tools as standard, and capable of moving from executive problem framing to solution architecture to hands-on build.

** Key Responsibilities*
* ** 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.

** Qualifications & Experience*
* ** Required*
* + 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.

** Preferred*
* + Experience in enterprise product development, consulting, or software with significant AI/ML components.

+ Familiarity with LLM application design, enterprise AI architecture patterns, and responsible AI principles.

+ Track record of taking AI initiatives from POC to production in complex organizations.

** Core Competencies*
* +  
** AI-Native Technical Depth:
** Practitioner-level understanding of how AI systems are built and deployed.

+  
** Product Engineering Mindset:
** Thinks in specs, prototypes, and iterations.

+  
** Executive Problem Framing:
** Identifies the problem worth solving and structures AI opportunities with both clarity and a value orientation.

+  
** Solution Architecture:
** Engages engineering leaders as a peer, not an intermediary.

+  
** Strategic Prioritization:
** Balances value, feasibility, and risk.

+  
** Trusted Advisor:
** Earns trust through depth, delivery, and integrity.

** What Success Looks Like*
* + Business leaders view the AIBP as a technical and strategic advisor, not a coordinator.

+ A prioritized portfolio of high-value AI initiatives is actively progressing.

+ POCs and pilots move into production with measurable business impact.

+ Engineering teams see the AIBP as a credible partner who accelerates delivery.

+ AI-first tools and practices become normalized across business units.

If you will be working at home occasionally or permanently, the internet connection must be obtained through a cable broadband or fiber optic internet service provider with speeds of at least 10

Mbps download/5

Mbps upload.

For this…