Top Tech Jobs & Startup Jobs in Denver & Boulder, CO

Drive ASI's growth in the energy sector by developing strategies, building relationships, identifying opportunities, and aligning customer needs with product capabilities.

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.

The Software Engineer develops web and software applications for MGMA utilizing C#, ASP.Net, SQL, and participates in an Agile development environment.

Design, develop, test, and deploy Go and Python microservices for a B2B financial platform. Collaborate cross-functionally, support client onboarding and documentation, build automations, monitor system reliability, and later transition to product development or team lead responsibilities.

Lead product strategy and execution for ITDR and ISPM offerings, manage a small product team, drive discovery through launch, collaborate with engineering, design, sales, and marketing, and measure product success with business metrics.

Negotiate delinquent accounts on behalf of clients to maximize savings, build and maintain relationships with external partners, manage client finances and account queues, use tools to consolidate debts for negotiation leverage, provide client guidance, and participate in special projects to support client outcomes.

Design, build, and own production AI agents and automations for marketing. Integrate and instrument the marketing stack (Salesforce, HubSpot, Qualified, Clay, ZoomInfo, data warehouse), implement predictive scoring and personalization, monitor systems for reliability, and collaborate with marketing, RevOps, and sales to translate problems into deployable software.

The Enterprise Account Executive will drive sales by managing the sales process, generating new business, engaging with prospects, and achieving revenue targets.

Own enterprise AI strategy and launch the PureSpectrum AI Academy. Curate an approved AI tool stack, create function-level AI playbooks, manage an active AI project portfolio, partner with engineering to implement API-connected workflows, and drive measurable adoption, automation, efficiency, and ROI across functions while reporting program status to leadership.

Design, prototype, and deploy LLM-powered agents, RAG workflows, and automations that accelerate internal teams and customer-facing product features. Integrate AI systems with SaaS tools, build reusable components and evaluation frameworks, embed with business teams to deliver measurable outcomes, and establish standards for responsible AI, monitoring, and cost control across the company.