• Lead pre-sales engagements, including discovery sessions, executive workshops, SOW scoping, and storytelling that connects services to measurable business outcomes • Own pipeline development for adoption and change offerings; build repeatable collateral, playbooks, and case studies • Define and refine the AI adoption and change management value proposition in partnership with Practice and Sales leadership • Influence pricing and packaging, balancing value, delivery feasibility, and margin • Serve as executive sponsor or engagement leader on key AI, LLM, and data adoption programs; own delivery quality, risk management, and business outcomes • Oversee change roadmaps, stakeholder analyses, communications strategies, enablement plans, and adoption KPIs; ensure AI initiatives are paired with the operating model and role changes needed to realize value • Coach project managers, change leads, and technical teams to unblock delivery, manage resistance, and protect timelines and scope • Own satisfaction, renewal, expansion, and referenceability for change and adoption engagements • Build trusted advisor relationships with executive client sponsors (CIO, CDO, CAO, CHRO, BU leaders), shaping multi-phase roadmaps from pilot to scale • Track adoption KPIs (usage, behavioral change, time-to-value, productivity lift, AI literacy) and drive voice-of-customer feedback into offerings and delivery methods • Create and sponsor thought leadership, frameworks, blueprints for agentic AI and LLM adoption, and reusable assets (diagnostic tools, maturity models, training curricula, stakeholder playbooks) • Mentor and develop a bench of change management practitioners; define long-term talent strategy for the capability • Contribute to practice strategy, annual planning, and delivery methodology governance; champion a "run on AI / deliver with AI" culture

• Define and drive the technical roadmap for AI, ML, and data systems, overseeing development, deployment, and operationalization to ensure robust performance, scalability, and direct alignment with key business strategy and requirements. • Lead, mentor, and grow a small high-performing team of data scientists and ML engineers, cultivating a culture of technical excellence, accountability, and continuous learning. • Direct the entire lifecycle—from design to deployment—of robust data pipelines, scalable model training, and innovative AI/ML applications. • Guide the development, tuning, deployment, and MLOps of Machine Learning models for cybersecurity. • Architect, govern, and optimize large-scale, high-performance data pipelines essential for securely and efficiently processing massive vulnerability, asset, and activity datasets. • Collaborate closely with infrastructure teams to architect AI workloads and data pipelines that meet stringent requirements for security, efficiency, and scalability, particularly within multi-tenant and regulated environments. • Serve as the primary technical subject matter expert and liaison.

Family Medicine Physician (Multiple Positions) – Group Health, Inc. dba HealthPartners (St. Paul, MN). Provide primary medical care and treatment in a clinic-based practice within the subspecialty of geriatrics, caring for medically fragile populations who are at higher risk of having age-related diseases. Requires MD/DO or equivalent, Family Medicine Residency, BE/BC in Family Medicine, and MN medical license. May permit telehealth. $250,000/year. As a HealthPartners colleague, we’re committed to nurturing your diverse talents, valuing your dedication, and supporting your work-life balance. We offer a comprehensive range of benefits to support every aspect of your life, including health, time off, retirement planning, and continuous learning opportunities. Our goal is to help you thrive physically, mentally, emotionally, and financially, so you can continue delivering exceptional care. Apply at Family Medicine Physician (multiple positions) - HealthPartners/GHI Careers

• Design and implement AI agent architectures that can understand user requests, reason through complex problems, and execute multi-step plans • Develop frameworks for AI agents to interact with various tools, APIs, and services • Create mechanisms for effective human-AI collaboration, including clarification, feedback, and guidance • Optimize agent performance for reliability, accuracy, and efficiency • Build monitoring and evaluation systems to assess agent performance and identify areas for improvement • Collaborate with cross-functional teams to integrate agents into products and workflows • Stay current with the latest research and developments in AI agent technology