Top Biotech Jobs in Denver & Boulder, CO

Leads measurement and product marketing for eight enterprise AI platforms. Builds shared KPI, taxonomy, scorecard, data-quality, and value-realization frameworks; translates usage and outcome data into executive insights and investment guidance. Oversees positioning, internal launches, campaigns, enablement, adoption, and audience segmentation. Partners across product, engineering, data, communications, and business teams while building and managing teams responsible for analytics, marketing, and communications.

Drive new client acquisition and revenue through high-volume lead outreach, sales strategy, CRM pipeline management, client pitches, stakeholder engagement, pricing analysis, and cross-functional collaboration to meet sales targets.

Lead customer implementations of SOPHiA GENETICS genomic analysis solutions, from planning and sample selection through configuration, training, adoption, and issue resolution. Manage MaxCare Program schedules, timelines, sampling strategies, Statements of Work, technical setup, and cross-functional delivery. Translate laboratory, bioinformatics, data, and clinical regulatory requirements into practical solutions while building trusted customer relationships. The field-based US role includes approximately 30% travel.

Leads Inato’s marketing organization and strategy, including account-based marketing for enterprise sponsors, integrated sales campaigns, product positioning, go-to-market execution, customer marketing, and advocacy programs. Establishes marketing goals and metrics tied to business outcomes while partnering with Sales, Product, Customer Success, Strategy, and executive leadership. Coaches and develops the marketing team, builds internal product marketing capabilities, and drives measurable pipeline creation, customer expansion, and market differentiation.

Lead complex clinical assay development projects from inception to commercialization, managing scope, budget, timelines, and cross-functional teams while ensuring compliance with industry regulations and fostering team development.

Lead enterprise AI solution architecture across reusable capabilities, defining engineering patterns, integration designs, deployment strategies, security controls, monitoring, lifecycle management, and technical standards. Partner with application, platform, infrastructure, data, DevOps, security, and delivery teams. Contribute hands-on to proof-of-concepts and production AI solutions while guiding technology adoption and enterprise AI roadmap decisions.

Own and evolve enterprise AWS infrastructure, governance, security, identity, networking, and shared platforms. Build and operate full-stack services in TypeScript and Python, automate infrastructure and delivery, improve monitoring and reliability, manage incidents and on-call operations, and establish audit-ready controls. Partner across engineering and IT, improve production readiness, and mentor engineers while delivering secure, scalable, low-blast-radius systems.

Own the hardware portfolio strategy and roadmap for wearable healthcare devices. Lead product development with engineering, design, regulatory, and clinical teams; define positioning, value propositions, pricing, forecasting, and business cases; analyze customer insights and competition; integrate wearables with software, mobile, RTLS, and connectivity platforms; and monitor portfolio performance KPIs.

Develops and supports data architecture and medical imaging informatics solutions on the XNAT platform. Responsibilities include data integration, modeling, storage and delivery optimization, data-sharing, coding, testing, release management, defect reduction, technical documentation, and partner support. The role collaborates with research and clinical teams, oversees stable XNAT releases, and advances platform capabilities. Required qualifications include a bachelor’s degree or equivalent experience, five years of data-related experience, and PostgreSQL skills.

Build and operate MLOps infrastructure for scientific discovery platforms, including model deployment pipelines, registries, monitoring, APIs, cloud-native serving, CI/CD, and observability. The role operationalizes computational biology, cheminformatics, and related scientific models for researchers and AI agents, ensuring scalable performance, versioning, reliability, uncertainty metrics, and robust integration with data pipelines.