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

Owns the infrastructure and production lifecycle for product and marketing machine learning models. Responsibilities include real-time model deployment, feature pipelines and stores, monitoring and alerting, CI/CD, retraining infrastructure, marketing model operationalization, data pipelines, ad-platform feedback loops, and dependency management. The role bridges data science and engineering while mentoring teammates and making pragmatic architecture decisions.

Own the product modeling roadmap and end-to-end lifecycle of production machine learning models, including recommenders, routing, and agent assignment. Engineer features, design experiments, deploy iterative improvements, and define real-time model integration with engineering and product teams. Apply Bayesian methods, causal inference, and marketing measurement while translating uncertainty into business recommendations. Mentor teammates and raise data science standards through code review and documentation.

Lead sales agent onboarding, ramp, skills training, coaching, and remedial development across direct-to-consumer sales teams. Build training curricula, refine scripts, analyze AI-generated call insights, run script experiments, enable managers, and translate product and sales-floor feedback into actionable training. The role requires hands-on facilitation, sales acumen, autonomous program building, and continuous measurement and improvement of agent performance.

Own Ethos’s offline marketing strategy, budget, measurement, and growth across TV, streaming, podcasts, radio, and direct mail. Drive scalable customer acquisition through channel planning, media buying, vendor negotiation, performance optimization, testing, and cross-functional collaboration. Balance direct-response efficiency with long-term brand impact using MMM, geo-testing, lift studies, and halo analysis. Provide strategic recommendations to senior leadership while managing partners, forecasting investments, and identifying new channels and formats.

Develops direct-response copy for direct mail and paid social advertising, including headlines, offers, body copy, and calls to action. Creates and tests messaging hypotheses, analyzes performance metrics, collaborates with design and marketing teams, and ensures persuasive copy complies with legal and regulatory requirements. Uses AI tools to generate and refine concepts while tailoring messaging to diverse life insurance audiences.

Leads organization-wide SRE strategy and builds reliable, scalable AWS and Kubernetes infrastructure. Establishes SLOs, observability, incident response, disaster recovery, and cost optimization practices. Develops AI gateways with governance and security controls, internal developer platforms, CI/CD tooling, and automation to reduce toil. Partners across engineering, mentors SREs, influences technical direction, and leads complex infrastructure initiatives.

Design, build, test, deploy, and support Salesforce applications and integrations. Develop Apex, LWC, Flow solutions, REST APIs, event-driven integrations, and secure data workflows. Ensure bulk processing, governor-limit compliance, automated testing, retries, idempotency, and failure recovery. Manage Git-based CI/CD deployments, troubleshoot production issues, review code, and collaborate with administrators, analysts, data engineers, and product teams.

Lead the development of Ethos’s sales training and enablement system across direct-to-consumer insurance sales. Own sales scripts, AI-powered call insights, experimentation, agent onboarding, remedial training, coaching programs, and manager development. Partner with Sales and Product leadership to improve customer engagement, conversion, agent performance, and sales strategy. Build measurable systems for script adherence, call analysis, ramp performance, and organization-wide manager coaching.

Leads the Policy Administration team, overseeing daily operations, staffing, escalations, customer support procedures, and policy servicing. Drives process improvement, workflow innovation, issue resolution, and cross-functional collaboration with product, engineering, compliance, sales, underwriting, and carrier partners. Monitors metrics, prepares reports, uses data to guide decisions, manages Jira tickets, and recruits and develops team members. Requires life insurance knowledge, operational leadership, process improvement experience, and Salesforce or comparable support software proficiency.

Leads cross-functional technical programs from planning through launch, including carrier integrations, partner launches, internal tooling, and platform improvements. Partners with Engineering, Product, Data, Operations, and external stakeholders to establish milestones, manage risks and dependencies, communicate program health, make technical tradeoffs, and improve execution through retrospectives and success metrics.