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Growing together. The Director, AI Transformation, Medicare Sales Digital & Technology Experience will lead the transformation and delivery of a core suite of established and emerging AI products across the Medicare shopping and sales ecosystem. The role will connect experiences serving consumers, field agents, external distribution partners, internal telesales representatives, and Producer Help Desk teams into a cohesive, intelligent product portfolio.
This leader will shape how AI capabilities share trusted knowledge, apply persona-specific context and skills, preserve journey state, and support seamless transitions from one channel or tool to another. The goal is a simpler shopping experience that reduces repeated work, accelerates answers, improves consistency, and enables timely next-best-action recommendations while retaining appropriate human judgment and control.
This is not an innovation lab role. It is an enterprise product transformation and delivery role accountable for moving a portfolio of AI-enabled experiences from fragmented capabilities toward a unified, scalable operating model. The successful candidate will combine modern digital product leadership, technical fluency, engineering partnership, and user-first experience judgment with a bias toward shipping, measurement, and continuous improvement.
You'll enjoy the flexibility to work remotely * from anywhere within the U. S. as you take on some tough challenges. Primary
Unified AI Product Strategy & Portfolio Leadership Define and execute a unified product strategy for AI-enabled Medicare shopping, sales, agent, partner, and support experiences Own the integrated portfolio vision, product principles, sequencing, dependencies, and measurable outcomes across digital direct-to-consumer, Jarvis, eAlliance, telesales desktop, and broker-help desk experiences Translate business strategy, user needs, technology capabilities, and market signals into a clear multi-year transformation roadmap and near-term delivery priorities Rationalize overlapping capabilities, reduce duplicated solutions, and identify where shared platform services should replace channel-specific implementations Establish clear portfolio governance, decision rights, investment recommendations, and executive communications AI Voice, IVR & Human Connection Experience Own the product strategy for AI Voice and conversational IVR capabilities that support Medicare education, guided decision support, intent capture, navigation, and appropriate routing Design web and mobile experiences that allow shoppers to initiate or schedule a voice connection with telesales, including browser-based calling or comparable digital-to-voice pathways where supported by the approved technology ecosystem Ensure relevant shopper progress, preferences, questions, and completed steps can be made available to the receiving telesales workflow, subject to consent, privacy, security, and platform constraints Define experiences in which an AI voice assistant can educate or guide a shopper, collect approved information, resolve appropriate needs, or transition the interaction to a licensed human agent Create clear escalation, opt-out, authentication, consent, disclosure, and recovery patterns so users understand when they are interacting with AI and can reach a person when needed Partner with contact center, telephony, Amazon Connect, CRM, digital, data, architecture, and operations teams to align call routing, journey context, agent desktop integration, and service reliability Apply conversational design, speech recognition, natural language understanding, voice user-interface, latency, accessibility, and call-quality considerations to product decisions Measure containment or completion only alongside customer understanding, successful routing, handoff quality, agent readiness, compliance, and overall journey outcomes Connected Shopping Journey & Experience Transformation Create a coherent end-to-end experience that allows consumers and sales professionals to move across digital, agent-assisted, partner, and service touchpoints without unnecessary loss of context or repeated data entry Define cross-channel journey patterns for education, needs capture, provider and prescription inputs, plan comparison, assistance, enrollment, follow-up, and servicing transitions Ensure each experience applies the right persona, permissions, language, context, skills, and workflow for the user while drawing from a common intelligence foundation Partner with experience design and research leaders to continuously observe users, identify friction, validate improvements, and protect simplicity as the ecosystem grows Champion human-centered experiences that make AI helpful, explainable, accessible, and easy to recover from when confidence is low or human support is needed Shared Knowledge, Skills & AI Orchestration Lead the evolution of common knowledge services and reusable AI skills that deliver consistent, current, and governed answers across channels Define how persona-specific context, journey state, business rules, permissions, and interaction history are applied without creating separate intelligence stacks for every tool Guide orchestration patterns that support intent recognition, retrieval, task completion, next-best-action recommendations, and handoffs between AI and human-assisted experiences Create product requirements for context continuity and interoperability so relevant information can follow the journey across approved systems and channels Partner with data, architecture, AI, compliance, and operations teams to establish feedback loops, evaluation methods, confidence thresholds, and human-in-the-loop controls Modern Product Delivery & Engineering Transformation Introduce modern product and engineering practices that increase delivery speed, product quality, learning velocity, and accountability Build durable partnerships with engineering, architecture, platform, data, design, research, and operations leaders, aligning teams around outcomes rather than isolated feature delivery Use AI-assisted software development tools and practices, including coding agents such as Claude Code and Codex, to improve discovery, implementation, testing, review, documentation, and release readiness where enterprise standards permit Create clear product increments, acceptance criteria, evaluation plans, release gates, and observability requirements for AI-enabled capabilities Reduce handoff friction across business, product, design, engineering, and technology teams through shared artifacts, rapid decisioning, and transparent ownership Coach teams toward smaller releases, faster feedback, automated quality practices, disciplined experimentation, and continuous delivery Product Operations, Measurement & Optimization Establish a common product operating system spanning intake, discovery, prioritization, roadmaps, delivery, release, adoption, support, and lifecycle management Define outcome metrics across consumer and agent experience, answer quality, speed to resolution, self-service, handoff success, adoption, conversion support, productivity, and operational reliability Use product telemetry, user research, interaction analysis, and frontline feedback to identify friction and prioritize improvements Create transparent portfolio reporting that connects delivery progress to user and business outcomes Build mechanisms to identify, contain, and correct inaccurate, low-confidence, inconsistent, or high-friction AI experiences Responsible AI, Risk & Operational Readiness Ensure AI-enabled product experiences align with Responsible AI principles and applicable legal, regulatory, compliance, privacy, security, accessibility, and records requirements Partner with business and technology controls teams to integrate governance into the product lifecycle rather than treating review as a final-stage activity Ensure clear human escalation, override, auditability, feedback, and issue-management pathways within critical shopping and selling journeys Lead readiness across training, communications, support, release management, monitoring, and peak-season operations Balance transformation speed with the reliability and trust required for Medicare sales experiences People Leadership & Transformation Influence Lead and develop a high-performing multidisciplinary product organization with strong product judgment, technical fluency, delivery discipline, and customer empathy Create clarity across teams by defining mission, outcomes, roles, decision rights, and shared ways of working Influence senior business and technology leaders across a matrixed organization and resolve competing priorities through evidence and transparent tradeoffs Attract modern product and delivery talent while elevating the capabilities of existing teams through coaching and hands-on leadership Model urgency, curiosity, accountability, humility, and a willingness to challenge legacy assumptions in service of users and outcomes You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
Required
Bachelor's degree or equivalent practical experience 5+ years of demonstrated experience in artificial intelligence (AI), machine learning, generative AI, AI agents, or related technologies. Expertise may be acquired through professional experience, graduate research, academic achievement, open-source contributions, certifications, entrepreneurial ventures, or independent projects Demonstrated success transforming a digital product organization or complex product portfolio within a modern, technology-enabled company Experience leading multiple customer-facing and employee-facing digital products through strategy, delivery, adoption, optimization, and lifecycle decisions Proven ability to connect product experience, platform architecture, data, AI, and engineering delivery into a cohesive roadmap Solid technical fluency with modern software delivery, APIs, cloud platforms, data products, AI architectures, product telemetry, experimentation, and quality practices Working knowledge of conversational AI and voice experience concepts, including IVR, contact center integration, speech recognition, natural language understanding, call routing, digital-to-voice handoffs, and agent desktop connectivity Hands-on familiarity with AI-assisted development tools and agentic engineering workflows, such as Claude Code, Codex, or comparable coding agents Experience leading cross-functional product, design, engineering, data, and operations teams in a large, matrixed environment Exceptional ability to simplify complexity, make decisions with incomplete information, and communicate clearly with executives and delivery teams Demonstrated user-first product judgment, delivery discipline, and success improving speed without sacrificing quality or trust
10+ years of experience in digital product management, software product development, technology transformation, platform leadership, or related roles Experience in healthcare, Medicare, insurance, financial services, travel, retail, or another complex and highly regulated consumer industry Experience modernizing digital shopping, marketplace, commerce, customer service, contact center, CRM, or sales enablement ecosystems Experience building multi-persona p