Top Tech Jobs & Startup Jobs

Lead candidate experiences for the United States talent market from Mexico City. Responsibilities include candidate screening, shortlisting, interview coordination, communications, offer extensions, employer-brand representation, Workday data maintenance, stakeholder partnership, and recruitment process improvement. The role requires strong recruiting experience, U.S. market expertise, advanced English, applicant tracking system knowledge, and interest in using artificial intelligence and technology to improve hiring outcomes.

Leads the development, deployment, and integration of scalable AI and machine learning solutions across business units. Drives generative AI and LLM innovation, collaborates with US commercial and India-based data science teams, and champions experimentation, adoption, and continuous improvement. The role requires hands-on technical involvement, cross-functional communication, and strategic application of advanced foundation models, recommendation systems, and next-best-action capabilities.

Manage global customs classification, origin determination, import and export declaration checks, trade compliance reporting, and KPIs. Advise stakeholders on international trade requirements, identify and escalate compliance risks, prepare reports, and improve customs processes. The role requires collaboration across regions and functions, strong analytical accuracy, and support for health, safety, and environmental objectives.

Manages international customs and trade compliance activities, including customs classification, origin determination, post-entry declaration checks, export licensing support, KPI reporting, and compliance risk escalation. Advises business stakeholders on trade regulations, collaborates across global functions, prepares reports, and contributes to process improvement. The role requires strong analytical accuracy, communication skills, and knowledge of international trade and customs processes.

Drives territory sales growth by identifying high-potential healthcare customers, building compliant relationships with healthcare professionals and medical influencers, and delivering personalized customer engagement. Uses customer and territory insights to prioritize accounts, address unmet patient and customer needs, coordinate with cross-functional teams, and support product-related initiatives. Maintains ethical standards and promptly reports technical complaints, adverse events, and special cases related to company products.

Leads enterprise analytics engineering by establishing statistical standards, validation and QA practices, measurement frameworks, reporting standards, governance, reusable data pipelines, automation, and production-grade analytics solutions. Connects Commercial, Medical, Market Access, and other teams to enable scalable, trusted, compliant, and decision-focused analytics. Requires strong technical and cross-functional leadership, analytics infrastructure expertise, and the ability to build enterprise capabilities from ambiguity.

Leads the long-term strategy, innovation roadmap, and ecosystem partnerships for NovaOS, an enterprise AI platform. Identifies emerging technologies and market opportunities, develops AI-enabled concepts and business cases, manages strategic partnerships, and transitions validated innovations into product roadmaps. Establishes governance and investment frameworks, collaborates with Product, Applied AI, Engineering, UX, and Commercial teams, and builds a high-performing strategy and innovation organization.

Apply advanced AI/ML methods to multi-modal preclinical, clinical and real-world datasets to enable target and biomarker discovery. Develop and deploy generative and foundation models, collaborate cross-functionally, and publish scientific results.

Designs, builds, and governs enterprise ontologies, taxonomies, semantic models, knowledge graphs, metadata services, and semantic APIs. Partners with product, AI, analytics, platform, and business teams to enable RAG, agentic AI, contextual search, reasoning, interoperability, and analytics consistency. Establishes metadata governance, quality controls, stewardship, lifecycle management, and reusable engineering patterns. Evaluates semantic technologies, mentors engineers, and communicates technical trade-offs and recommendations to diverse stakeholders.

Leads enterprise strategy, architecture, governance, and implementation for semantic layers, knowledge graphs, ontologies, taxonomies, and AI-enabled knowledge capabilities. Partners with AI, data science, product, engineering, and business teams to enable trusted AI, analytics, search, interoperability, and reusable knowledge. Establishes metadata and knowledge lifecycle standards, advances RAG and semantic search innovation, and builds a high-performing team of semantic and knowledge engineers.