• AI Enablement and Strategy: Lead organization-wide AI adoption and enablement initiatives. Identify opportunities to leverage AI tools to improve efficiency, accuracy, and productivity across business units. • Solution Design and Prototyping: Architect, configure, and prototype solutions using LLMs, APIs, and orchestration tools. Develop proof-of-concepts for department-specific AI use cases. • Systems Integration: Integrate AI capabilities into existing applications, workflows, and cloud environments (e.g., Azure, AWS). Manage connections between enterprise systems and AI platforms through APIs or automation layers. • AI Platform Management: Oversee configuration and operational support of platforms such as OpenAI, Anthropic, Zapier, and Make. • Security and Compliance Oversight: Ensure AI implementations adhere to internal policies and external standards, including HIPAA, ISO 27001/27002, and internal data governance frameworks. • Responsible AI and Risk Management: Implement and promote compliance with frameworks such as NIST AI RMF 1.0 and the EU AI Act. Conduct AI risk assessments and recommend mitigation controls. • Cross-Functional Collaboration: Partner with department heads and technical teams to evaluate requirements, recommend AI-enabled tools, and support implementation. • Education and Advocacy: Serve as a trusted AI advisor to business and technical leaders. Provide internal guidance, training, and documentation on AI tool usage, safety, and best practices. • Performance Monitoring: Establish metrics to evaluate AI-driven efficiency gains, user adoption, and business impact. • Vendor and Tool Evaluation: Continuously research, evaluate, and recommend new AI tools, frameworks, and integration strategies aligned with enterprise goals.

• Design and build the orchestration and planning systems that power Dropbox’s agent platform, including task decomposition, scheduling, and error recovery. • Implement real-time execution frameworks that allow multiple agents and tools to coordinate and act reliably at scale. • Develop clean, extensible APIs, data models, and protocols that enable new agent capabilities to plug seamlessly into the platform. • Build and maintain the evaluation platform used to measure agent performance (accuracy, latency, cost, safety, satisfaction) and catch regressions. • Establish and improve observability, testing, and debugging workflows for agentic systems in production. • Collaborate with AI research, infra, and product teams to translate high-level product goals and research insights into robust, production-ready systems. • Contribute to technical roadmaps, design docs, and architecture reviews, helping set direction for agent platform and eval platform evolution.

• Lead the design and delivery of automation and AI-driven solutions • Partner with stakeholders to uncover bottlenecks and scope priorities • Build end-to-end workflows and establish durable frameworks • Collaborate with Sales, RevOps, Product, and Data Engineering teams

• Design, implement, and maintain workflow automations and orchestration solutions using Camunda BPM, BPMN, DMN, and related components. • Develop integration layers, microservices, and APIs that interact with Camunda processes. • Enhance and optimize existing workflows for scalability, durability, and performance. • Troubleshoot and resolve workflow- or orchestration-related production system issues. • Collaborate with cross‑functional teams to translate business requirements into executable process models. • Contribute to CI/CD practices, automated testing, and version control for workflow assets. • AI‑assisted code generation with tools such as ChatGPT and GitHub Copilot.