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The role involves managing commercial partnerships for data collection in Mexico, overseeing partner relations, team leadership, and ensuring operational efficiencies.

Lead architecture and technical direction for Scale's Generative AI Data Engine, embedding into high-priority Contributor teams to unblock delivery, overhaul platform infrastructure for LLM-native workloads, ensure scalability/reliability, mentor engineers, partner with product/leadership, and own large end-to-end backend, frontend, and ML system initiatives.

Lead DoD account strategy to transition Agentic AI prototypes into program-of-record deployments. Own full sales lifecycle and multi-million dollar quota, draft proposals and white papers, negotiate with primes/SIs, co-design technical Agentic workflows, manage post-award transition and long-term expansion, and travel ~20-30% while based in the National Capital Region.

Lead the revenue accounting team, ensuring compliance with ASC 606 and U.S. GAAP, manage close activities, provide technical guidance, and collaborate on revenue metrics.

Design and implement core identity infrastructure for authentication and authorization. Build SSO, MFA, federated identity, and authorization systems (ReBAC/ABAC/RBAC). Create identity governance policies for compliance, integrate IAM with cloud services, and present technical guidance to stakeholders.

Lead and execute public sector compliance and A&A programs (FedRAMP, DoD SRG, NIST, CMMC). Manage controls mapping, gap analysis, evidence collection, POAMs, vulnerability management, and auditor coordination. Drive cross-functional control implementation, maintain security documentation and GRC tooling, expand certification portfolio, and support customer assurance and audit activities.

Lead cross-functional, end-to-end technical programs for robotics and physical AI. Align Engineering, Operations, Product, and GTM; define scope and schedules, manage dependencies and risks, create program documentation and executive updates, establish scalable processes, and execute hands-on to drive hardware-software systems from design to large-scale production.

Design and implement end-to-end features across front-end, back-end, and infrastructure for Scale's Generative AI Data Engine. Build scalable systems using TypeScript, MongoDB, Elasticsearch, and Temporal that handle millions of tasks weekly. Own high-impact revenue-critical systems, collaborate with model and cross-functional teams, and help shape engineering culture and best practices on a hybrid team in San Francisco or New York City.

Lead strategic planning and execution for the Scale Generative AI Platform, owning technical scoping, architecture, and production launches. Coordinate cross-functional teams (platform engineering, Core ML, Research, Product), translate infrastructure metrics into roadmaps, mitigate deployment risks, define SLOs, drive developer velocity, and report adoption and reliability metrics to executive leadership to ensure scalable, secure, production-grade GenAI infrastructure.

Own end-to-end delivery of enterprise AI programs: manage timelines, risks, dependencies, and cross-functional integration. Translate technical complexity for engineering and executives, modernize agile workflows, and define program health metrics to drive adoption and scalable, reliable agentic solutions.