Applied AI Director (Primarily Office)

American Family Insurance•Boston, MA

2d•$172,000 - $294,000•Onsite

About The Position

This position provides strategic leadership for applied AI, machine learning, and advanced analytics solutions that drive business performance and operational effectiveness. You will partner with business and technology leaders to define enterprise AI strategy and build the production-grade capabilities, ensuring solutions are valuable, adopted, responsible, and aligned to enterprise priorities. This Director will also lead teams responsible for applied AI solution delivery, process-level AI transformation, business-domain partnership, model and solution quality, shared AI product lifecycle execution, portfolio delivery, and continuous improvement of AI-enabled products and workflows. You will also work across Technology and business domains, including Information Security, Governance, Enterprise Architecture, Application Development, Digital Services, Infrastructure, Data Engineering, Product, Operations, Risk, Legal, and Compliance partners. The role also partners with external delivery, consulting, academic, and research partners.

Requirements

Demonstrated experience delivering AI, machine learning, or advanced analytics solutions into production business workflows.
Demonstrated ability to connect AI capabilities to measurable business outcomes and enterprise priorities.
Demonstrated experience leading process-level transformation, not only technology implementation.
Strong understanding of applied AI, machine learning, advanced analytics, experimentation, validation, and production adoption.
Experience with AI product lifecycle practices in a shared ownership model across business, data science, platform, product, portfolio, and external delivery partners.
Demonstrated experience partnering across Information Security, Governance, Enterprise Architecture, Application Development, Digital Services, Infrastructure, Data Engineering, Product, Operations, Risk, Legal, Compliance, and business teams.
Demonstrated ability to communicate complex technical concepts, tradeoffs, risks, and implications to non-technical and executive audiences.
Experience managing or partnering with external research, consulting, academic, or delivery partners.
Demonstrated ability to lead through ambiguity, emerging technology, growth, and organizational change.
Demonstrated effective people leadership, coaching, prioritization, and talent development skills.

Responsibilities

Lead applied AI solution delivery: Direct the development and delivery of applied AI, machine learning, and advanced analytics solutions that address high-value business problems. Ensure solutions are production-oriented, maintainable, measurable, and aligned to enterprise priorities.
Advance process-level AI transformation: Partner with business and Technology leaders to identify, assess, and redesign high-value workflows where AI can improve speed, quality, consistency, cost-to-serve, or customer/employee experience. Assist teams connect individual AI capabilities into coherent business process journeys rather than isolated point solutions.
Shape AI opportunities and portfolio alignment: Partner with business, Technology, product, portfolio, and operations leaders to identify and prioritize applied AI opportunities. Remain in tune with frontier/evolving AI capabilities and emerging research in order to inform the approaching opportunities and long-term strategy. Translate ambiguous business needs into actionable AI solution opportunities, delivery roadmaps, and measurable outcomes.
Lead applied science and solution quality: Provide leadership over applied modeling, AI solution design, prompt and agentic workflow patterns, experimentation design, validation, and solution evaluation. Ensure teams use appropriate scientific, statistical, engineering, and product practices for the problem being solved.
Partner on AI product lifecycle management: Work with business owners, product and portfolio leaders, AI Platform Engineering, and external delivery partners to shape AI product lifecycle practices from idea through production, adoption, continuous improvement, and retirement. Clarify lifecycle responsibilities across business, Applied AI, AI Platform Engineering, and delivery partners so accountability is shared and sustainable.
Drive value realization and adoption: Define success measures for AI solutions and ensure delivered capabilities are adopted, measured, iterated, and connected to business impact. Help business partners move from AI awareness to operational use and sustained value.
Develop reusable AI solution patterns: Identify repeated solution patterns across domains and partner with AI Platform Engineering to convert them into reusable frameworks, components, and delivery accelerators. Reduce one-off builds where shared approaches can improve speed, quality, governance, and long-term supportability.
Ensure operational handoff and ongoing solution improvement: Design applied AI solutions with supportability, escalation paths, and operational handoff in mind. Partner with AI Platform Engineering and business/product owners on L3 enhancements, bug fixes, upgrades, and solution-level improvements after production release.
Embed responsible AI and evaluation discipline: Embed responsible AI practices into applied AI delivery in alignment with enterprise governance expectations. Partner with business, governance, and platform teams to define domain-specific evaluation criteria that reflect standards for quality, accuracy, compliance, fairness, customer experience, and business usefulness.
Lead people and develop talent: Build and lead high-performing teams of data scientists, applied AI practitioners, and related specialists aligned with enterprise strategy. Set clear priorities, coach leaders and individual contributors, and create a collaborative, performance-driven, inclusive environment.