Top Remote Jobs in CO

Own and execute the activation roadmap to increase new-user activation and first-transaction rates. Analyze funnels, design experiments, write product requirements, run A/B tests with Data Science, partner with Engineering and Design, and maintain operational reliability for activation services.

Own and scale Coinbase's notification platform and experience to grow MAU, drive engagement, and maximize LTV using ML-driven personalization, analytics, and cross-functional execution.

As a Lead TMS Compliance Analyst III, you will conduct investigations related to transaction monitoring, ensure compliance with BSA/AML policies, document findings, and analyze transactions to determine legitimacy.

Build and manage a personalized wealth management practice through proactive client and prospect outreach, partner relationship development, tailored financial planning, and coordination with internal specialists for investment management, insurance, and estate planning to grow and preserve client relationships.

The Private Client Financial Advisor develops personalized wealth management strategies for clients, enhances partnerships for new business, and provides comprehensive financial services.

Branch-based Wealth Advisor who builds personalized wealth management plans, grows client relationships through outreach and referrals, coordinates with internal specialists for investments, insurance, and estate planning, and develops new business from partners and prospects.

Serve as Narmi's fraud subject-matter expert across pre-sales, onboarding, and post-live support. Advise customers on fraud strategy, configure fraud tools, partner with Sales and Product, influence roadmap, and expand adoption of fraud solutions like Narmi Guard.

The Enterprise Account Executive will drive new business growth by acquiring and expanding accounts, manage complex sales cycles, and collaborate with teams to meet customer needs in cybersecurity.

Own the vision and roadmap for Huntress's internal data platform and data products. Drive data quality, governance, self-service analytics, and cross-functional adoption. Translate business needs into data product requirements, lead stakeholders, and prioritize initiatives to enable scalable, governed, and AI-enabled data solutions.

Own full-cycle recruiting for complex engineering roles, partner with engineering leaders to build pipelines and hiring strategies, screen and assess candidates, lead offer and closing processes, and use data and AI tools to improve sourcing and hiring outcomes.

As a PhD Systems & AI/ML Research Intern, you'll work on infrastructure problems, build prototypes, run benchmarks, and document findings.

The Senior iOS Engineer will enhance the design system by building reusable iOS components, collaborating with cross-platform teams, and ensuring accessibility, performance, and documentation standards are met.

Serve as an enterprise-level strategic advisor to executive customers, aligning business objectives with integrated, multi-practice technology strategies. Lead executive discussions, quarterback complex cross-practice opportunities, translate goals into IT roadmaps, quantify ROI, partner with sellers on large deals, and mentor the strategist community.

This role is responsible for designing, implementing, and maintaining DB2 software solutions for Managed Services clients, providing technical leadership, and ensuring successful service delivery.

The AI Platform Administrator will monitor, maintain, and optimize AI platforms, assist with deployment, provide user support, and document processes.

Lead go-to-market efforts targeting large Medicare agencies and national call centers: generate leads via in-person and virtual outreach, run product demos, negotiate contracts, close deals, and coordinate onboarding with Sales, Marketing, and Agent Success teams to scale enterprise partnerships.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

Build and own full-stack UX and backend systems for the ML lifecycle: design architecture, integrations, observability, CI/CD, and production frontend/backends. Lead technical initiatives, mentor engineers, and collaborate across teams to scale ML platform capabilities.