• Maintain deep expertise in one or more AI technology areas. • Clearly present and communicate relevance of technological advances as relevant to our work in biostatistics, bioinformatics and data science at Exact Sciences. • Develop perspectives on “AI technology affordance”: what do these advances in AI technology allow us to do (more efficiently and / or more effectively) that we couldn’t do before. • Work with stakeholders to discover and refine requirements for ML- and AI-based solutions to business problems with a focus on bioinformatics, biostatistics and data engineering applications. • Collaborate with other ML/AI engineers and relevant partners to design software solutions that utilize state-of-the art artificial intelligence and machine learning techniques. • Work with other AI and ML engineers and software engineers to implement and deploy ML and AI solutions. • Work in an Agile framework focused on iterative, rapid delivery of proof-of-concept solutions. • Contribute to the development of an AI strategy at Exact Sciences that empowers the team to leverage both existing AI and ML tools and those developed in-house to accelerate and enhance bioinformatics, biostatistics and data science processes and outcomes. • Contribute to internal initiatives to build training resources, develop knowledge bases, and educate on advanced AI and ML technologies and best practices for leveraging them. • Provide mentorship and coaching to more junior level team members. • Act as resource and subject matter expert in core team and/or cross-functional meetings. • Exercise discretion and judgment within broadly defined practices and policies in selecting methods and techniques and evaluation criteria for obtaining and interpreting results. • Ability to apply strong communication skills and to explain difficult, sensitive, and/or complex information to audiences of peers. • Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork. • Support and comply with the company’s Quality Management System policies and procedures. • Maintain regular and reliable attendance. • Ability to act with an inclusion mindset and model these behaviors for the organization. • Ability to work designated schedule. • Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 85% of a typical working day. • Ability to travel 5% of working time away from work location, may include overnight/weekend travel.

• Lead planning and execution of complex AI/ML projects in life sciences • Collaborate with biostatisticians and data scientists • Design software solutions utilizing AI methodologies • Set up Agile frameworks for rapid solution delivery • Provide leadership in AI strategy development • Mentor junior team members • Contribute to intellectual property portfolio • Uphold company values through accountability and inclusion

• Design, evolve, and scale the Customer Success AI platform, including reusable services and reference architectures that support multiple AI products and internal AI experiences • Build and maintain foundational AI infrastructure such as orchestration services, context engines, memory services, workflow execution frameworks, enterprise integrations, and scalable architectures for multi-agent systems • Optimize platform capabilities across model routing, latency, cost, reliability, observability, governance, and security to ensure enterprise-grade performance and resilience • Lead technical architecture and engineering standards across multiple AI products, mentoring AI Engineers and driving engineering excellence through reusable frameworks, patterns, and platform capabilities • Partner cross-functionally with Product Management, Engineering, IT, Security, Data, and Customer Success teams to evaluate emerging AI technologies, shape adoption strategy, and align platform evolution with long-term business and enterprise architecture needs

• Design, build, and deploy AI-powered solutions using the Hatz AI platform as the primary solution • Assess customer data sources and requirements to determine solution architecture, and establish secure, compliant data pipelines connecting customer systems to AI workflows • Serve as the active deployment resource for customer AI requests, executing technical implementations of AI Agents, Workflows, and Applications in production environments • Maintain deep proficiency with the Hatz AI platform as NetCov's primary AI solution • Maintain working knowledge of the Microsoft Co-Pilot and Anthropic Claude ecosystems — integration points, deployment models, API capabilities, and common use cases • Troubleshoot customer-managed Co-Pilot and Claude deployments on request and help customers optimize existing Microsoft and Anthropic AI investments • Evaluate requests across all three platforms to recommend the best solution architecture, including when to migrate workloads between platforms • Evaluate customer data sources for quality, completeness, and AI suitability, and work with customers to remediate issues affecting solution performance • Design data validation, cleansing, and preparation workflows, and establish architecture patterns that separate, secure, and govern customer data across Hatz, Co-Pilot, and Claude • Document data source specifications, transformation logic, and governance policies for each deployment • Ensure data handling aligns with customer compliance requirements, privacy regulations, and NetCov security policies; identify gaps requiring project work or vendor solutions • Monitor and respond to customer-facing AI tickets in HaloPSA, assessing scope, classification, and platform selection • Provide technical troubleshooting, data diagnostics, and optimization recommendations • Deliver timely, high-quality solutions that align with service level agreements, communicating any data quality or architectural constraints that may impact feasibility • Identify requests that warrant formal projects rather than support tickets — complex data integration, platform migrations, multi-platform initiatives — and advise the SVP of Innovation on qualification, scope, and resourcing • Define and refine HaloPSA ticket categories for AI services, including multi-platform support, and track reporting metrics — platform usage and support volume by ecosystem — to inform team growth, hiring, and process improvements • Generate and track reporting metrics to inform process improvements, including platform usage patterns and support volume by AI ecosystem • Identify patterns in customer requests, platform preferences, and pain points that signal market demand and opportunities for deeper engagement across all three ecosystems • Apply advanced prompt engineering techniques optimized for Hatz AI, Co-Pilot, and Claude, and understand each platform's strengths, limitations, and use case alignment • Champion AI security and data governance standards across all deployments • Document solutions, configurations, and lessons learned to build organizational knowledge, and stay current with AI/ML developments, platform updates, and industry best practices • Work closely with the AI & Development Director to align deployments with internal development roadmaps and data architecture standards • Coordinate with cross-functional teams on internal and client-facing initiatives, communicating requirements, data needs, and progress to stakeholders at all levels • Collaborate with customer IT and data teams on existing data systems, governance policies, and AI deployments; coordinate with Microsoft and Anthropic support as needed