Top Hybrid Jobs in Denver & Boulder, CO

Partner with financial institutions to assess technical needs, deliver tailored product demos, respond to RFPs, and coordinate with product, implementation, and customer success to drive deals and revenue growth. Serve as the technical bridge between prospects and internal teams.

Lead operational risk management for Workplace Solutions globally, assessing risks for new initiatives, overseeing risk assessments and testing, reviewing loss events, supporting regulatory deliverables, engaging with horizontal risk programs, preparing materials for governance forums, and promoting a strong operational risk culture across regions and stakeholder groups.

Manage a portfolio of 70–90 small business clients, deliver tailored business banking and cash management solutions, identify credit opportunities up to ~$500K, build relationships through in-person client calls, collaborate with internal partners, and follow risk and regulatory protocols.

Manage and deepen a portfolio of ~100 business clients (>$5M revenue), drive deposit acquisition, cash management and credit opportunities up to ~$15M, deliver tailored financial advice, collaborate with specialists, protect the firm via risk controls, and cultivate referrals and cross-sell opportunities.

The VP of Agentic Systems will lead data science research and development, focusing on AI systems to enhance cybersecurity operations, requiring strong leadership and collaboration across technical teams.

Lead global Customer Success analytics strategy, architect data and health/adoption models, oversee data pipelines, deliver executive-level storytelling, mentor an analytics team, and drive cross-functional KPI alignment and self-serve BI adoption.

Build and maintain cloud cost monitoring, alerting, and optimization tooling. Develop automation, cost allocation/tagging, data pipelines, dashboards, and integrations with billing APIs. Support FinOps processes, implement cost guardrails, troubleshoot cost systems, participate in on-call rotation, and collaborate with senior engineers and product teams to drive cost-efficient infrastructure and reporting.

Lead and grow a US-based data science team while remaining hands-on: design, build, deploy, and maintain production ML models; write code; implement MLOps on GCP/Vertex AI; mentor junior data scientists and ML engineers; establish workflows, standards, and code repositories; translate business problems into rapid, production-grade data science solutions.

Manage paid search, social, and app acquisition across North America. Execute strategy and day-to-day on Google Ads, Apple Search Ads, Meta, Snap, TikTok, X, Reddit. Lead associates, optimize budgets and campaigns, drive conversion and YoY digital KPI growth, implement advanced measurement (MTA, MMM, incrementality), work with MMPs, and collaborate with brand, CRM, and global teams.

Handle escalated multi-channel customer inquiries (billing, renewals, cancellations, RMAs), mentor peers, manage high-volume cases, improve processes, and provide actionable insights to improve customer experience and retention.

Build automated reliability and self-healing platform tooling to protect production at scale. Improve incident management, reduce alert noise, evolve observability (monitoring, SLOs, performance detection), and develop AI-driven operational automation. Partner with product teams to diagnose reliability gaps, drive incident prevention, and champion operational excellence and best practices across engineering.

Develop, train, and optimize computer vision and ML models (particularly video-based safety) using petabyte-scale camera and sensor data. Deploy and optimize models for backend and edge inference, collaborate with cross-functional teams, and translate customer needs into scalable ML/CV solutions.

Own and improve end-to-end payroll and partner operational processes across CX. Design scalable workflows, define SLAs and escalation paths, coordinate incidents, analyze data for trends and risks, and drive cross-functional process standardization using Zendesk, Slack, Asana, and related systems.

Provide technical support and escalations for payroll customers: troubleshoot payroll runs, taxes, benefits, integrations, and data flows; advise on payroll configurations and compliance; partner with Product and Engineering to drive improvements and prevent payroll risks.

Lead development and support of enterprise insurance applications on the Microsoft .NET stack. Design, build, and maintain secure, scalable systems and integrations, troubleshoot production issues, modernize architecture and cloud adoption, and improve CI/CD and automated testing while collaborating with product, project, and business stakeholders.

Grow and manage a book of affluent and complex-client relationships through proactive outreach, discovery-driven advice, and multi-product solutions across deposits, lending, investments, and business banking. Coordinate with Wealth, Home Lending, and Business partners, document planning conversations, champion digital adoption, ensure accurate risk/compliance documentation, and support branch service needs. Must obtain/maintain required FINRA and state insurance licenses and work a schedule that includes most Saturdays.

Manage and grow relationships with affluent customers, provide multi-product financial advice, acquire new clients, coordinate referrals with Wealth/Home Lending/Business Banking, handle everyday banking needs, ensure compliance and accurate documentation, and achieve retention and growth targets while supporting branch team and championing digital adoption.

Underwrite and monitor mid-corporate gaming credits: build and sensitize financial models, perform diligence, draft credit approval memoranda, manage closings, produce portfolio reviews, execute amendments/waivers, and integrate AI tools into workflows.

Own production health and performance for AI-enabled claims products across Disability & Leave. Monitor SLAs and UX, lead incident triage and RCA, prioritize fixes with engineering and operations, drive systemic improvements, and oversee FINEOS/Catalyst integration and optimization.

Lead intake, roadmap, and governance for an AI automation/platform team. Harden and ship business-built AI apps to production with secure GCP platforms, define acceptance criteria and responsible-AI gates, manage vendor buy-vs-build decisions, drive adoption, measure outcomes, and manage AI economics and stakeholder communication.

Build, model, and maintain scalable BigQuery-based data solutions on GCP. Implement performant data models, storage partitioning/clustering, ETL improvements, data validation, and documentation. Collaborate with architects, data scientists, and engineers to deliver governed, high-quality data for reporting and AI initiatives.