Top Remote Jobs in CO

Manage a team of TPRM analysts to run the vendor risk lifecycle, improve tooling and automation (ServiceNow TPRM, AI), perform assessments and audits, develop TPRM policies aligned to frameworks (NIST/ISO/SOC 2), partner with procurement/legal/IT, track KPIs, and support audit and reporting to leadership.

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.

Manage end-to-end California workers' compensation claims, including complex/high-exposure files. Conduct investigations, determine compensability, set reserves, manage medical and indemnity benefits, control litigation and legal costs, negotiate settlements, and provide excellent service to agents and insureds while mentoring junior adjusters and improving claims processes.

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.

Lead enterprise sales for JP Morgan Chase's Workplace equity compensation solution targeting pre-IPO companies. Build and close a pipeline, cultivate executive relationships (finance/HR), collaborate with internal banking, legal, product, and marketing teams, negotiate deals, and analyze sales performance to drive market expansion.

Lead applied AI/ML initiatives, design and deliver production-grade software, develop secure high-quality code, troubleshoot, automate remediation, evaluate vendor architectures, champion best practices across engineering, and drive adoption of AI/ML, NLP, LLMs and streaming technologies.

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.

Handle incoming owner relations inquiries about revenue, land, division orders, JIB, A/R, and A&P. Log and follow up cases in a tracking system, build trusting client relationships, manage difficult situations calmly, provide accurate timely responses, and participate in cross-training.

Design, build, and maintain high-throughput data ingestion and processing pipelines; integrate AI-powered infrastructure; implement and support complex computing algorithms and distributed services; own systems end-to-end including architecture, observability, reliability, and operational support; lead architectural initiatives and reduce system complexity while maintaining performance on large-scale real-time data.

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.

Serve as primary post-sales contact to drive onboarding, adoption, retention, and expansion for industrial cybersecurity customers. Build relationships, define success metrics, manage churn risk, monitor account health, execute success plans, maintain SFDC records, and collaborate with sales, TAMs, services, intelligence, and support.

Lead and manage an adversary hunting team focused on OT threat groups. Perform hands-on hunting using Synapse and Storm Query Language, produce WorldView reports and detection artifacts, collaborate with intelligence and malware analysis, refine KPIs, support incident response surges, recruit and develop staff, and represent the team externally.

Hunt, identify, and analyze adversary tools, malware, and tradecraft targeting ICS/OT. Develop and maintain analysis tools and scripts, contribute to threat assessments and customer advisories, leverage intel and network analysis tools, recommend automation and telemetry improvements, and support incident response and external communications.

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.