Role Description We’re looking for an AI Automation Specialist and AI Creators across Latin America to help streamline and scale business operations through cutting-edge AI tools and systems. This role is ideal for someone who goes beyond using AI—and actively builds, integrates, and optimizes automation workflows. You will be responsible for identifying opportunities to automate processes, implementing AI-driven solutions, and integrating them into existing systems. You’ll work cross-functionally to improve efficiency, reduce manual work, and unlock new capabilities across the business. Key Responsibilities - Leverage AI tools (e.g., ClawBot, Claude Code) to automate business processes - Research, test, and implement new AI technologies to improve efficiency and productivity - Build and integrate AI systems into existing workflows and infrastructure - Develop automation workflows, agents, or tools to streamline operations - Provide technical guidance and support to internal teams using AI systems - Continuously optimize and improve automation performance Qualifications - Hands-on experience with AI/ML tools and platforms (e.g., ClawBot, Claude Code) - Strong programming and software development skills - Proven experience building AI automations, workflows, or integrations - Ability to research, evaluate, and implement new AI technologies independently - Experience integrating AI systems into existing business processes - Strong problem-solving skills and a proactive mindset Requirements - USD Salary - Ability to work remotely

• Data collection, evaluation, and annotation. • Pairwise comparisons. • Counting tasks. • Object tagging and labeling across different content types (audio, video, images, or collected data)

• Own end-to-end execution of the AI Enablement Program: working group facilitation, use case pipeline management, adoption tracking, and executive reporting • Drive AI literacy and responsible use across a diverse workforce, meeting employees where they are and building capability without coercion • Design and deliver training and engagement programs calibrated to varied audience profiles and functional contexts • Manage the use case intake pathway from submission through scoring, cross-functional review, and outcome documentation • Coordinate with external AI strategy and implementation partners to maintain an integrated, non-duplicative delivery pipeline • Partner with Cybersecurity on AI tool security reviews, access control requirements, audit logging, and risk response protocols • Collaborate with Legal and Compliance on data privacy, IP risk, MNPI controls, and contractual obligations across AI deployments • Work with Data Engineering & Analytics to align AI tools with the enterprise data platform and govern data access across regulated and non-regulated environments • Engage Clinical Operations, Regulatory Affairs, and Medical teams to surface, prioritize, and advance AI use cases in trial and submission workflows • Partner with Finance, HR, Commercial, and G&A leadership on non-clinical use case discovery and deployment • Facilitate the AI Working Group, maintaining cross-functional accountability and structured deliberation on tool assessments and program priorities • Serve as the enterprise administer on the AI and agent tool landscape, owning tool selection, lifecycle management, and the capability roadmap across LLM platforms, agentic workflows, productivity tools, and clinical AI applications • Evaluate net-new tools and agentic frameworks through the governance assessment pathway before deployment; maintain the approved tool inventory with current risk classifications • Manage vendor relationships, contract terms, and licensing decisions in coordination with Finance, Legal, and Procurement • Stay ahead of capability shifts in the agent ecosystem and proactively surface opportunities. • Administer the AI Governance Framework: Approved Systems Registry, risk classification tiers, and GxP and non-GxP assessment pathways • Ensure AI deployments meet applicable regulatory, privacy, and data integrity standards, and support audit readiness across GxP-adjacent environments • Evolve governance controls as the tool landscape and regulatory environment change. • Define and own program success metrics, such as adoption rates, use case throughput, time-to-assessment, literacy baselines, and quantified efficiency gains by function • Establish a reporting cadence to leadership and the Governance Committee with clear narrative on program ROI and risk posture • Maintain a use case outcomes repository to capture lessons learned and identify replication opportunities across the organization • Benchmark Apogee’s AI maturity against clinical-stage biotech peers and industry best practice to prioritize program investments

• Solve business problems by applying daily AI (LLMs, no-code tools). • Identify and prioritize use cases, prototype them, and bring them to a working state. • Ensure the independent use of AI across business functions. • Define, evaluate, and manage metrics for the effectiveness of daily AI implementation (P&L, customer metrics, employee performance, etc.). • Drive the development of an internal AI community focused on business challenges. • Monitor the AI tools market and integrate solutions to address business challenges.