• Architect and maintain enterprise-grade ML infrastructure, including model versioning, automated testing frameworks, containerization strategies, CI/CD pipelines, and comprehensive monitoring systems for model performance, data quality, and drift detection • Drive MLOps strategy and standards across the organization • Mentor data scientists and engineers on production best practices, system design, and scalable architecture patterns • Own the complete journey from model development through production deployment, including real-time and batch inference systems, A/B testing frameworks, and automated retraining pipelines • Collaborate with clinical leaders, product teams, and data scientists to translate complex healthcare requirements into robust, scalable ML solutions • Present technical strategies to executive stakeholders • Build fault-tolerant, compliant systems that meet healthcare security and privacy standards • Establish SLAs, incident response protocols, and disaster recovery procedures for mission-critical ML services • Evaluate and integrate cutting-edge MLOps tools and practices • Design systems that scale with Monogram's growth while reducing operational overhead and improving model iteration velocity

Role Description This is a senior individual contributor role on the Identity Platform team, responsible for defining and delivering the product strategy for non-human identity. You will own the roadmap for how the platform authenticates, authorizes, and governs machine identities and AI agents alongside the human identities it supports today. This includes vendor evaluation, proof of concept leadership, and build vs integrate decisions, as well as close partnership with security, architecture, AI platform, and engineering teams to establish identity’s role in this space. There is no established playbook—you will create it. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. - Own the end-to-end product strategy and roadmap for non-human identity capabilities. - Drives execution by identifying and shaping initiatives across multiple teams, ensuring alignment and progress through influence, rather than direct ownership of delivery. - Define identity’s role across authentication, authorization, and governance for machine identities and AI agents. - Translate ambiguous problem spaces into clear product direction, priorities, and trade-offs. - Lead vendor landscape evaluations and build vs buy decisions. - Drive execution across engineering, security, architecture, and AI platform teams without direct authority. - Communicate strategy and decisions effectively to senior stakeholders. Qualifications - 10+ years of product management experience in platform, infrastructure, or enterprise systems. - Ownership of at least one zero to one product or capability, from definition through delivery or scale. - Experience making enterprise-level product decisions (e.g., vendor evaluations, build vs buy). - Working knowledge of identity systems, including authentication and authorization models (RBAC/ABAC). - Active, hands-on use of AI tools in professional work. - Proven ability to influence without authority across multiple teams. Requirements - Experience with non-human identity, workload identity, or agentic AI. - Experience operating in enterprise scale or regulated environments. - Technical background as an engineer or architect. Benefits - Comprehensive benefits package. - Incentive and recognition programs. - Equity stock purchase. - 401k contribution (all benefits are subject to eligibility requirements). Application Deadline This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.

• Design, build, evaluate, and ship agentic based features and interactive experiences to bring our products to the next level • Collaborate with cross functional teams spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and useful ways • Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users • Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization • Actively contributed to a strong community of machine learning practitioners at Spotify

• Design, build, and deploy LLM-powered product features, including lab result summaries, clinical workflow tools, and practitioner-facing conversational agents. • Build backend services that integrate LLMs and ML models into Fullscript’s platform, primarily using Python, with increasing exposure to Elixir as the platform evolves. • Develop AI systems that can support open-ended clinical questions, follow-up interactions, and reasoning over structured and unstructured healthcare context. • Implement prompting, grounding, retrieval, and safety strategies that improve output quality, consistency, and clinical relevance. • Build evaluation, testing, monitoring, and CI/CD workflows for AI features, including approaches for accuracy, hallucination detection, edge cases, and reliability. • Partner with medical, product, analytics, and engineering teams to translate clinical needs into practical AI capabilities that can scale. • Own AI systems end to end, from experimentation and prototyping through production deployment, iteration, and ongoing improvement. • Contribute to architecture and implementation decisions for AI-powered analytics, lab interpretation, and clinical decision-support workflows. • Stay current with fast-moving LLM, agentic AI, and applied ML ecosystems, while staying pragmatic about what is ready for production use.