• Define and execute a company-wide AI strategy aligned with Veryon’s business objectives • Partner with ELT and SLT to identify, prioritize, and roadmap AI initiatives across all departments • Partner with Security and Compliance teams to grow and ensure adherence of Veryon’s AI governance, best practices, and responsible AI usage • Drive organization-wide AI adoption, including training and change management initiatives • Identify and deliver measurable business value through AI-driven efficiencies and insights • Lead the integration of AI capabilities across Veryon’s product suite • Define and execute the roadmap for evolving products into agentic, decision-capable systems • Collaborate with Product and Engineering teams to prioritize and deliver AI-driven features • Ensure scalable & reliable deployment of AI/ML models in production environments • Evaluate and incorporate emerging AI technologies into the product strategy • Build, lead, and mentor high-performing AI/ML engineering teams • Drive cross-functional collaboration across all departments of Veryon including technology, product, sales, marketing, customer support, customer success, people operations and finance • Oversee the full lifecycle of AI solutions (design, development, deployment, optimization) • Establish KPIs to measure AI impact, adoption, and ROI • Manage partnerships with external vendors and AI technology providers • Build lasting relationships with large enterprise customers such as commercial aviation operators and OEMs • Apply aviation expertise to ensure AI solutions are operationally relevant and compliant • Identify opportunities to enhance maintenance, diagnostics, and operational performance • Align AI initiatives with aviation standards, safety, and regulatory requirements

• Design and implement AI Bench (AI Workbench) environments for experimentation and prototyping • Build standardized, reproducible AI development environments (notebooks, containers, IDEs) • Enable rapid prototyping using AI frameworks such as PyTorch, TensorFlow, and NVIDIA NeMo • Integrate AI benches with enterprise data platforms (Cloudera, Spark, Hadoop) • Configure and optimize GPU-enabled environments for training and experimentation • Support distributed AI workloads for research and early-stage model development • Provide self-service AI benches for data scientists and ML engineers • Implement environment versioning, dependency management, and reproducibility standards • Monitor bench usage, performance, and resource utilization • Ensure security, access control, and isolation across AI benches • Collaborate with AI Platform, Data, and MLOps teams to align bench capabilities.

• Uses SAS or other software to develop custom programming code to generate summary tables, data listings, graphs and derived datasets as specified in the statistical analysis plan and programming specifications. • Works to ensure that outputs meet quality standards and project requirements. • Performs validation programming and works with other Programmers, Biostatisticians, and other project team members to resolve discrepancies or any findings. • Keeps project team members informed of programming progress and issues requiring their attention. • Follows applicable SOPs, WIs, and relevant regulatory guidelines (e.g. ICH). • Maintains well organized, complete, and up-to-date project documentation, testing, and verification/quality control documents and programs ensuring inspection readiness. • Manages scheduling and time constraints across multiple projects at a time, sets goals based on priorities from management, and adapts to timeline or priority changes by reorganizing daily workload.

• Design, build, and refine autonomous AI agents using Salesforce Agentforce • Lead rapid prototyping efforts, validate AI feasibility in real systems • Troubleshoot complex multi-platform failures • Influence client outcomes and future Salesforce platform enhancements