Responsibilities

• Use Case Discovery & Solution Auditing (The Systems Thinker)
• Triage & Backlog Management: Actively partner with brand and business teams to audit their current workflows, identify bottlenecks, and surface high-impact AI opportunities (e.g., automated content variation, localized ad ops, predictive lead scoring).
• Solution Review: Evaluate existing or vendor-proposed AI tools to ensure they integrate seamlessly with our current MarTech stack without fracturing data workflows or violating security guardrails.
• Feasibility Guardrails: Filter opportunities into distinct buckets: "Quick wins" (low-code automation), "Strategic builds" (partnering with Data Science), or "Not viable."
• 2. Technical Prototyping & Agent Development (The Builder)
• Rapid Prototyping: Build and test AI-driven agents and intelligent automation workflows using APIs and orchestration frameworks approved by Brunswick Corporation.
• Production Integration: Operationalize and inject these AI prototypes into our core marketing systems (e.g., Marketo, Salesforce, CMS, and dynamic creative platforms) to ensure a frictionless user experience for frontline marketers. Ensure every production workflow has a named business owner and review cadence .
• Performance Monitoring: Set up basic observability tracking to ensure deployed agents are accurate, cost-effective, and performing as intended without "hallucination drift."
• AI Governance: Partner with cross-functional teams to operationalize responsible-AI guardrails across all deployed agents including: tool/vendor intake reviews, data-handling and PII boundaries, prompt and output logging, human-in-the-loop checkpoints, and a documented kill-switch protocol for any agent that drifts out of tolerance.
• 3. Tactical Deployment & Brand Enablement (The Program Manager)
• Run Agile Sprints: Own the execution roadmap by managing 2-week agile sprint cycles to move AI solutions rapidly from ideation to active deployment within business units.
• Playbook Creation: Translate successful deployments into repeatable, documented playbooks, governance decision trees, and self-service templates so other brands can adopt them autonomously.
• Hands-on Hypercare: Embed with brand teams during early deployment phases to troubleshoot, gather immediate feedback, and optimize solutions in real-time.
• Adoption: Drive sustained usage by running brand-embedded enablement programs, office hours, and a marketing AI Champions network across divisions and COE.
• Community Building : Lead onboarding for new tools and proactively identify low-adoption pockets to coach teams through resistance, skill gaps, or workflow friction.
• Prompting : Structure, standardize and continuously refine a shared prompt and pattern library.
• 4. Reporting & Value Realization
• Transparency : Own the AI COE value narrative by building and maintaining a leadership-ready dashboard that tracks adoption metrics (active users, % of teams onboarded ), efficiency outcomes (hours saved, cycle-time compression), and solution health (accuracy, incident counts, etc.).
• Socialization : Deliver a monthly scorecard and quarterly business review that translates technical output into measurable enterprise impact for marketing leadership and the broader executive team.