• Review oncology patient records to determine whether cases meet clinical and payer policy requirements. • Serve as an escalation point for complex cases that cannot be accurately classified by AI workflows. • Analyze challenging clinical scenarios, including patients with multiple cancer diagnoses, complex treatment histories, and ambiguous documentation. • Document findings and recommendations within internal systems including Salesforce, LIMS, and other workflow tools. • Ensure accuracy and consistency of clinical review outcomes. • Perform ongoing audits of AI-generated clinical determinations and data classifications. • Evaluate AI performance against established clinical review standards. • Identify errors, trends, and opportunities to improve automation accuracy. • Participate in validation activities for new AI models, workflows, and clinical review processes. • Provide structured feedback to improve future AI performance. • Partner with Product, Engineering, and Data Science teams to improve clinical AI capabilities. • Help define clinical decision logic and requirements used in AI-driven workflows. • Translate clinical review findings into actionable recommendations for automation improvements. • Support testing and implementation of new AI-enabled solutions. • Contribute to the long-term evolution of Natera's oncology clinical intelligence platforms. • Develop expertise in payer coverage policies relevant to our Signatera product and oncology testing. • Evaluate clinical documentation against coverage requirements. • Assist in identifying cases that may require additional clinical review or reimbursement support. • Stay current on evolving oncology standards, treatment pathways, and reimbursement trends.

Role Description As the Director, AI Transformation, you'll own the strategy, execution and adoption of AI across ActivTrak. You'll lead a small team and serve as the connective tissue between the AI solutions we build and the employees who use them. This is a player-coach role: you'll set direction and represent AI transformation at the leadership level, while staying close enough to the work to build, test and iterate alongside your team. Key Responsibilities - Strategy & Roadmap: - Define and maintain the AI transformation roadmap, aligned to operational priorities across Revenue, Data, BI, and go-to-market functions. - Establish OKRs for AI adoption, productivity impact, and tool ROI, and report progress to the senior leadership. - Evaluate, recommend, and govern the AI tool stack, balancing capability, cost, and organizational readiness. - Identify the highest-leverage AI use cases across business functions and sequence delivery based on impact and feasibility. - Hands-On Delivery: - Build, prompt, and iterate on AI solutions directly by working in the tools. - Design and deploy agentic AI workflows that automate multi-step processes across business functions. - Work fluently with Model Context Protocol (MCP) servers to connect AI models to internal systems, data sources, and third-party tools. - Use AI coding tools (including Claude Code and GPT Codex) to accelerate solution development, automate scripts, and build internal tooling. - Partner with the AI Admin on integrations, prompt libraries, and production readiness for new solutions. - Lead proof-of-concept work on emerging AI capabilities, stress-testing tools before broader rollout. - Bring GTM systems fluency to revenue-adjacent use cases, including CRM automation, pipeline intelligence, and sales workflow optimization. - Team Leadership & Cross-Functional Influence: - Manage and develop a small team, setting clear scope, priorities, and success metrics for each role. - Create a high-trust, high-output team culture grounded in curiosity, iteration, and business impact. - Recruit and onboard future team members as function grows. - Governance & Compliance: - Own the AI governance framework for the organization. - Define policies for acceptable use, data handling, model selection and vendor risk across all AI tools and workflows. - Establish guardrails for agentic AI systems, ensuring automated workflows have appropriate human-in-the-loop checkpoints. - Partner with Legal, Security, and IT to ensure AI integrations meet data privacy, compliance and information security standards. - Stay current on the evolving regulatory landscape around AI and proactively surface business implications. - Maintain a clear inventory of all AI tools, integrations, and MCP connections in use across the organization. - Cross-functional influence: - Serve as the primary point of contact for all AI needs across ActivTrak. - Own and run the AI steering cadence: facilitate cross-functional meetings with business leads. - Lead up effectively, presenting roadmaps, risks and recommendations to senior leadership. - Influence without authority across peer functions. - Represent the AI Transform function in leadership forums and communicate progress, priorities and risks. Qualifications - 7 years in operations, RevOps, GTM strategy or technology transformation, with at least 2 years managing people or leading a function. - Demonstrated hands-on experience implementing AI solutions in a business context. - Fluency with modern AI platforms and the GTM stack: LLMs, no-code/low-code automation, CRM AI features, sequencing tools, enrichment platforms and attribution systems. - Working knowledge of agentic AI concepts and architectures. - Familiarity with MCP (Model Context Protocol) or equivalent integration patterns. - Hands-on experience with AI coding tools such as Claude Code, GPT Codex or similar. - Demonstrated understanding of AI governance and compliance considerations. - Active learner who stays current on the fast-moving AI landscape. - SaaS company experience strongly preferred. - Clear, confident communicator who can translate technical concepts for non-technical stakeholders. - Change management intuition. - High ownership orientation. Benefits - Competitive compensation and benefits. - Minimal travel. - Limited physical demands. Company Description This is an incredible opportunity to build something from the ground up at a work intelligence company that's defining how organizations understand people, applications, and AI tools. If you have a proven track record of creative thinking, a drive for learning, and a deep commitment to collaboration, we want to talk to you! ActivTrak is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. ActivTrak does not discriminate on the basis of race, color, religion, sex, national origin, political affiliation, sexual orientation, marital status, disability, age, protected veteran status, gender identity, or any other factor protected by applicable federal, state, or local laws.

• Design, develop, and maintain **AI- and automation-driven solutions** that support the rapid configuration of MCP for client implementations. • Leverage **LLMs (e.g., OpenAI, Claude)** to interpret client documentation (e.g., underwriting guidelines, product matrices, policies) and generate configuration outputs. • Build and optimize **automated workflows** using tools such as **n8n, Power Automate, Zapier**, or custom scripts to streamline repetitive tasks in the implementation lifecycle. • Integrate outputs with system APIs to **populate configuration templates and system admin screens**. • Partner with subject matter experts to **identify high-impact use cases** and translate business needs into scalable technical solutions. • Collaborate with Product and Engineering teams to ensure solutions are **secure, compliant, and maintainable**. • Create internal documentation, **training materials**, and guides to support adoption and enable team self-sufficiency. • Stay current on AI/automation trends and proactively propose **new tools or approaches** that can drive efficiency.

• Help shape the future of AI by designing challenging math problems that test and improve reasoning in cutting-edge models • Design advanced mathematical problems for frontier AI training and evaluation • Create deterministic problems with exactly one correct answer • Write complete, verified solutions and clearly document the reasoning process • Develop problems that test deep mathematical reasoning, not just memorization • Where relevant, use Python or specialized tools to build computational workflows • Ensure all outputs are technically precise, reproducible, and well-written in English