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

Design and develop scalable C++ software for endpoint state and control across Windows, macOS, and potentially Linux. Build reliable, multi-process systems that enforce endpoint behavior, manage local state, support IPC, and operate across millions of devices. Responsibilities include implementing features, improving platform performance, writing design documents, defining architecture and IPC contracts, and making technical decisions in an evolving, sparsely documented environment.

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.

Leads AI-driven revenue enablement programs for sales teams, using call, CRM, pipeline, and performance data to identify execution gaps and build workflows that improve rep productivity and behavior. Owns product launch enablement, everboarding, skills development, manager coaching, certifications, and process adoption. Measures impact through adoption, win rate, ACV, pipeline conversion, ramp time, and productivity metrics while partnering with Sales, Product Marketing, RevOps, and senior executives.

Manage inbound homeowner leads through the full sales cycle for Hometap's home equity investment product. Serve as primary contact from first call to close, maintain a high-volume pipeline in Salesforce and internal systems, coordinate with underwriting and processing teams, meet monthly and quarterly sales targets, and ensure compliant, empathetic communication throughout the application process.

Own a portfolio of major technology alliances, developing joint business plans, driving field-level co-selling, generating partner-sourced pipeline and revenue, and executing joint marketing programs. Align executives, sales, marketing, product, and partnerships teams around shared goals. Initially operate as an individual contributor, then hire and lead Technology Partner Managers while establishing team structures, QBRs, planning cadences, and reporting processes.

Own end-to-end network reliability across data centers, AWS, and GCP, including routing, switching, DNS, load balancing, service mesh, VPNs, circuits, and cross-connects. Automate network configuration with Ansible, Terraform, GitOps, CI validation, and IPAM. Engineer failover, observability, security hardening, client connectivity, and Kubernetes ingress while participating in an interrupt-contained on-call rotation.

Administer and enhance Edmunds’ Databricks data platform and AWS infrastructure. Build and maintain ETL pipelines, infrastructure-as-code tooling using Terraform or CDK, and operational dashboards, alerts, and reports. Collaborate with business, engineering, analytics, security, and infrastructure teams to support data platform users and AI solutions. Evaluate new technologies, troubleshoot platform issues, and improve operational, cost, and security visibility.

Manages 30–50 high-value enterprise clients by building stakeholder relationships, promoting client success, identifying growth and churn-mitigation opportunities, monitoring account health, resolving booking and reservation-management issues, and communicating platform expertise and industry trends. The role requires strong analytical, problem-solving, organizational, collaboration, and client-service skills, with regular use of Excel and Tableau.

Lead tax information reporting and withholding compliance across domestic and international frameworks, including FATCA, CRS, CARF, DAC7, and U.S. tax rules. Advise product teams on digital asset reporting, oversee tax documentation, withholding, remittance, and annual filings, and partner with technology and operations teams on automated workflows. Lead audits, risk remediation, policy updates, regulatory monitoring, and business requirements development for tax systems.

Architects and develops AI-powered systems, tools, agents, backend services, APIs, and experimentation frameworks using foundational AI models. Integrates AI capabilities with microservices, AWS, Snowflake, and complex data systems while ensuring scalability, reliability, and maintainability. Translates business problems into technical solutions, prototypes AI applications, collaborates with product and engineering teams, evaluates emerging AI technologies, and documents system designs and integration patterns.