Top Natural Language Processing Jobs in Denver & Boulder, CO

Leads internal communications for a rapidly scaling, distributed technology company. Builds communication systems, channels, and cadences; partners with executives on employee messaging; translates complex business and technical information; supports culture, employee experience, company narrative, and major company moments; and uses data and AI to improve communication effectiveness.

Partner with enterprise financial firms to design and implement scalable practice management programs. Lead executive engagement, success roadmapping, content and curriculum development, and live facilitation. Drive adoption through program design, data-driven recommendations, and feedback to Product. Travel regularly to client sites and industry events to deliver sessions and represent Zocks as a subject-matter expert.

Lead full-cycle B2B sales growth across K12 and higher education markets. Manage pipelines, territory strategy, consultative selling, enterprise negotiations, RFPs, procurement, forecasting, and quota attainment. Coach sales teams, present AI-enabled education solutions to institutional leaders, navigate privacy and compliance concerns, and collaborate with Customer Success, Product, and Marketing.

Leads the technical direction, architecture, and delivery of developer-facing desktop, web, and MCP surfaces for Pfizer’s internal developer platform. Provides hands-on software engineering leadership, ensures secure and privacy-first designs, guides cross-team delivery, mentors engineers, oversees code quality and DevOps practices, and leads incident response and continuous improvement. The role influences teams without direct reports and requires expertise across frontend, desktop, backend, developer tooling, enterprise software delivery, and technical architecture.

Own end-to-end localization operations for enterprise clients, serving as the primary operational contact and trusted advisor. Coordinate stakeholders and cross-functional teams, manage localization workflows and configurations across TMS and project tools, resolve client and internal issues, and improve processes through documentation, automation, and AI-enabled solutions. The role requires localization or translation project management experience, client communication skills, familiarity with localization formats and CAT/TMS tools, and strong organizational abilities.

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.

Leads end-to-end business transformation projects and workstreams, managing scope, schedules, budgets, risks, resources, stakeholders, reporting, and quality. Facilitates cross-functional collaboration across Operations, IT, Finance, vendors, and business teams. Oversees process redesign, systems implementation, organizational change, adoption, stage reviews, go/no-go decisions, and post-implementation lessons learned. Requires strong project governance, communication, change management, and delivery skills across Agile and waterfall environments.

Manage and mentor Azure-focused consulting teams, act as a billable Azure Architect (targeted 75% utilization), drive client engagements, oversee delivery and utilization, conduct 1:1s and training plans, contribute to pre-sales, estimate work, resolve personnel issues, and help define client experience and engagement processes.

Lead and grow ReflexAI’s platform engineering: design and automate multi-cloud (GCP/AWS) infrastructure, build developer tooling and CI/CD golden paths, improve observability and on-call ergonomics with Datadog, and strengthen cloud security, secrets management, and compliance to support production-grade AI workloads.

Leads Covera Health’s approximately 30-person Engineering, AI, and Platform/IT organization. Owns architecture, engineering standards, technical execution, reliability, security, data platforms, and production systems while partnering with the CPTO on strategy. The role requires hands-on technical leadership, development of engineering managers, cross-functional collaboration, recruitment and retention, and oversight of scalable healthcare data and AI platforms. The leader will remain involved in architecture reviews, technical decisions, complex data challenges, and critical production incidents.