Top Natural Language Processing Jobs in Denver & Boulder, CO

Own partner-network relationships after agreement signing, managing onboarding, contractual commitments, co-marketing, advisor adoption, and network penetration. Drive net-new bookings, expansions, trials, conversions, webinars, demos, and enablement activities. Track activation and pipeline metrics in Salesforce, coordinate with strategic partnerships, marketing, sales, account management, RevOps, and product teams, and forecast bookings across multiple financial-advisor networks.

Drive Superhuman Mail’s mid-market expansion through value-based B2B SaaS sales. Responsibilities include managing complex, multi-stakeholder deal cycles, negotiating contracts, building executive relationships, developing outbound strategies and account plans, forecasting, maintaining pipeline rigor, and collaborating with Sales Development, Customer Success, Sales Engineering, and Product teams.

Designs and maintains automated test frameworks and exploratory suites for products, APIs, SDKs, AI models, and data platforms. Develops functional, integration, end-to-end, regression, API, browser, load, and reliability tests; creates datasets, evaluation pipelines, dashboards, and CI/CD release gates. Partners across Engineering, Research, Product, Data, and Infrastructure to validate model behavior, data quality, performance, and production readiness. Documents reproducible defects, supports triage, and communicates risks.

Leads Pfizer’s global customs governance and compliance framework, including Belgian Authorized Economic Operator status, internal controls, customs valuation reporting, audits, continuous improvement, and stakeholder partnerships. Provides technical expertise in customs law and operations while implementing standardized, automated workflows aligned with GDP, GMP, and local regulations. Oversees talent development, performance standards, budgeting, and strategic customs initiatives across global operations.

Develop product launch narratives and messaging that connect with customers and prospects. Create demos, case studies, webinars, campaigns, web content, and customer stories. Partner cross-functionally with product, sales, and customer success to ensure consistent positioning. Conduct customer and prospect research, identify market trends, and use data-driven insights to strengthen product marketing strategy.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

Lead an established RevOps and Enablement team to sharpen analytics, harden systems and data architecture, and scale AI-first workflows across Sales, Marketing, and CX. Own revenue tech stack, forecasting, GTM reporting, process optimization, and enablement programs while partnering with executive leadership to drive measurable revenue outcomes.

Generate qualified sales pipeline through outbound prospecting and inbound lead qualification. Communicate Nightfall’s AI-native data loss prevention value to security, compliance, and engineering stakeholders. Partner with Account Executives to schedule meetings and provide clean lead handoffs, maintain accurate CRM activity, and improve outreach using performance data and feedback.

Build Nightfall AI’s revenue operations and GTM engineering function from scratch. Own CRM architecture, forecasting, quota and territory planning, reporting, GTM data quality, automation workflows, process design, and cross-functional alignment across Sales, Marketing, Customer Success, and Finance. The role requires hands-on development of AI-enabled GTM automations, strong revenue analytics, and strategic partnership with executive leadership in a high-growth B2B SaaS environment.

Lead global partner lifecycle for Federal and European Systems Integrators: recruit and onboard partners, build strategic relationships, enable partner sales, execute co-sell strategies, align cross-functionally with product and marketing, and establish KPIs to measure partner productivity and pipeline impact.

Leads the architecture, delivery, and technical strategy for enterprise AI solutions, including generative AI, intelligent agents, data platforms, and cloud-native applications. Advises executive clients, oversees large-scale AI programs, establishes Azure-based architectures and engineering standards, mentors technical teams, and advances responsible AI, MLOps/LLMOps, security, scalability, and reusable intellectual property across the practice.