• Build trusted relationships with C-suite and senior stakeholders • Map and manage relationships across business, technology, and procurement leaders • Serve as a strategic advisor within the account • Apply deep insurance industry knowledge • Understand client business models, challenges, and goals • Align AI solutions to deliver measurable Business Value • Develop and maintain comprehensive strategic accounts plans • Define and execute growth strategy within assigned accounts • Own overall account expansion roadmap • Lead full Sales lifecycle from Discovery to SOW • Identify and develop new opportunities (net-new work) • Expand existing engagements and bodies of work • Proactively introduce new ideas and solutions • Position cutting-edge services aligned to client needs • Drive business performance improvements for clients • Partner with technology leaders and solution experts • Engage global delivery teams to ensure committed results • Align internal stakeholders to client strategy • Focus on measurable business outcomes • Drive customer satisfaction • Ensure delivery excellence and long-term partnership growth

• Lead and develop the Enterprise AI Adoption Team • Hire, mentor, and develop a team of AI Adoption Managers responsible for onboarding EvenUp’s enterprise customers. • Coach team members on executive communication, change management, and driving adoption across complex organizations. • Establish performance metrics focused on activation speed, product adoption, and early customer outcomes. • Foster a culture of ownership, curiosity, and continuous improvement across the team. • Build and scale enterprise adoption programs • Design and refine scalable onboarding playbooks that ensure enterprise customers achieve value within their first 30 days. • Define best practices for guiding firms through operational and workflow changes required to adopt EvenUp’s AI platform. • Partner with Product and Data teams to define the key adoption metrics that signal long-term success. • Continuously improve onboarding programs based on customer feedback, product usage data, and field insights. • Drive strategic customer outcomes • Partner with Sales during the late stages of enterprise deals to ensure smooth transitions into onboarding and activation. • Support your team in managing high-stakes customer relationships, including executive stakeholders at major law firms. • Ensure enterprise customers experience a seamless transition from sales to adoption to long-term customer success. • Step in directly on critical or complex accounts to help unblock challenges and ensure successful adoption. • Cross-functional leadership • Serve as a key voice of the customer during the earliest stage of product usage. • Partner closely with Sales, Sales Engineering, Customer Success, Product, Engineering, Legal/Medical Operations, and Technical Program Managers to improve the onboarding experience. • Identify product gaps, friction points, and opportunities to improve the first-time user experience. • Help influence product direction based on insights gathered from real customer adoption patterns.

• Use customer and employee feedback, alongside operational data and insights, to inform improvements to the HR experience, quality, and outcomes. • Align initiatives with departmental strategic objectives and provide expert judgement on risk, compliance, and scalability, ensuring statutory and employment-related regulatory requirements are embedded directly into automation and system design decisions. • Scope and deliver as the Directly Responsible Individual (DRI) multi-phase initiatives across process redesign, tooling, and change management from planning, prototype, launch and optimization. • Map operational processes, identify bottlenecks, and architect end-to-end automated workflows that increase speed, accuracy, and scalability. • Build and maintain data pipelines via native connectors or APIs across HRIS, case management, payroll, and other tools to ensure seamless data flow, event triggers and reporting. • Leverage low-code/no-code platforms (like Zapier, Make, Retool, n8n or similar) to prototype and deploy rapid automations. • Deploy and govern AI tools or agents (e.g., for document processing, query triage, policy guidance, data auditing) that enhance efficiency, compliance and user experience. • Design and Implement multi-agent patterns (e.g. maker/checker setups, routing to specialised agents) and governance policies (e.g. retries, fallbacks, guardrails), embedding appropriate human oversight in employment-related workflows to ensure compliant and responsible AI deployment. • Build and maintain automation observability and governance (e.g. tracing, logging, agent runs evaluation) including access controls and auditability suitable for HR data. • Develop and maintain fit-for-purpose operational data models to support reporting, audit, compliance and data integrity initiatives within HR Operations. • Build and iterate on HR Operations analytics dashboards and reports (e.g. data audits, performance metrics) using SQL and BI tools such as Tableau or Sigma. • Foster strong cross-functional collaboration and support effective change management, training, adoption and continuous improvement of AI & Automation driven solutions. • Serve as a technical lead for AI & Automation within the Ops departments, contributing to the evolution of best practices and ways of working. • Mentor and guide junior team members, supporting capability uplift and operational maturity across the department.

• Lead the design and implementation of AI-enabled automation strategies to enhance enterprise technology services and operational efficiency. • Identify opportunities to automate repetitive processes, service desk operations, and data workflows using AI and intelligent automation technologies. • Implement automation-first approaches across enterprise platforms, leveraging machine learning, predictive analytics, and intelligent agents to improve service delivery. • Establish best practices for responsible AI adoption, governance, and operational integration. • Implement AI-powered service management capabilities, including virtual agents, automated troubleshooting tools, and predictive issue detection. • Develop automation solutions that reduce service desk workload through self-service tools, chatbots, and intelligent routing of support requests. • Use AI-driven analytics to identify service trends, root causes of incidents, and opportunities for operational improvement. • Monitor performance metrics for automated service capabilities to improve response times, resolution rates, and user satisfaction. • Design and implement automated workflows and integrations between enterprise platforms using APIs, event-driven automation, and orchestration tools. • Develop automation pipelines that connect enterprise applications, cloud services, and collaboration platforms. • Implement automation-as-code practices using CI/CD pipelines, workflow orchestration tools, and automation frameworks. • Integrate AI capabilities into enterprise SaaS platforms to improve productivity, collaboration, and decision-making. • Lead development of AI-powered analytics capabilities to extract insights from operational and enterprise data. • Develop predictive models, statistical analysis tools, and machine learning workflows that support data-driven decision-making. • Design and implement data pipelines and analytics platforms that support real-time and batch processing of enterprise data. • Develop dashboards and visualization tools that allow leadership to monitor performance metrics, operational trends, and program outcomes. • Enable predictive insights that support mission-critical decisions and improve operational performance. • Establish frameworks for secure, scalable AI implementation across enterprise technology platforms. • Ensure automation solutions align with enterprise architecture, cybersecurity requirements, and data governance policies. • Implement monitoring tools to track AI system performance, model accuracy, and automation effectiveness. • Develop governance policies for the responsible use of AI and automated decision-support tools. • Work closely with engineering, cybersecurity, service operations, and data teams to integrate AI capabilities across the enterprise environment. • Communicate complex AI concepts and automation strategies to technical and non-technical stakeholders. • Provide training and guidance to teams on automation tools, AI platforms, and intelligent workflow solutions. • Support cross-functional teams in identifying automation opportunities and implementing scalable solutions.