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

Recruit clinicians by reviewing applications, conducting interviews, assessing clinical and operational fit, maintaining accurate applicant-tracking records, and coordinating candidate handoffs through offer and onboarding stages. The role focuses on delivering an excellent candidate experience while identifying therapists and psychologists passionate about serving older adults. This is a remote, part-time position requiring strong interpersonal judgment, organization, flexibility, and the ability to manage frequent interviews in a fast-paced environment.

Owns executive relationships and revenue growth for 2–4 high-value enterprise accounts. Develops multi-year account plans, expands product adoption, identifies cross-sell and upsell opportunities, leads renewals and contract negotiations, and coordinates Product, Marketing, Client Success, and Solutions teams. The role also conducts strategic business reviews, represents the company with senior stakeholders, and drives profitable long-term partnerships across Roadside Assistance and Accident Management offerings.

Lead technical strategy and execution for multi-quarter initiatives, build and maintain software systems using AI, mentor and elevate engineers, collaborate across disciplines, and protect user privacy and security. The role involves working in an AWS and Kubernetes environment with technologies including Python, TypeScript, React, Go, Airflow, dbt, and Claude Code.

Build and maintain Customer Success and Implementation playbooks, SOPs, training programs, knowledge bases, presentation materials, and scalable workflows. Partner cross-functionally to communicate process and product changes, improve automation and efficiency, identify customer risks, and measure enablement effectiveness. Support implementation, launch readiness, customer health, escalations, business reviews, renewals, and expansion.

Drive new-business SaaS revenue through account and territory planning, prospect research, business development, and field sales. Build trusted relationships with C-suite stakeholders, map client relationships, coordinate cross-functional resources, advise customers on IT roadmaps, and identify specialists to support deals. The role requires negotiating agreements, achieving sales targets, maintaining executive relationships, and promoting a collaborative customer-success focus.

Build and ship production AI systems across retrieval, knowledge graphs, inference, agentic workflows, and data platforms. Develop customer-context retrieval, scored signals, evaluation and observability capabilities, and workflows that turn insights into action. Work hands-on with large and small models, durable orchestration, cloud deployment, inference-cost optimization, and high-volume observability data. Establish reusable engineering patterns, collaborate with product and platform teams, and mentor through strong technical contributions.

Administers and analyzes sales compensation programs, including commission payout processing, data auditing, dispute resolution, plan modeling, reporting, and dashboard maintenance. Partners with sales, finance, and HR teams to ensure accurate payouts, compliance, documentation, and process improvements. Requires strong Excel modeling skills, CRM and incentive compensation platform experience, analytical ability, communication skills, and independent judgment.

Own end-to-end onboarding for complex enterprise ranching customers across multiple sites. Build rollout plans, manage executives and field teams, lead training and change management, resolve deployment issues, coordinate cross-functional partners, and optimize onboarding processes for scalable adoption. The role combines strategic stakeholder management with hands-on field work and requires regular travel to customer ranches.

Design, build, and operate high-throughput, low-latency ad-serving infrastructure processing millions of requests per second. Optimize GPU-powered TensorRT inference, feature stores, model serving, benchmarking, experimentation tooling, and system reliability. Partner with machine learning engineers to productionize models and own systems through design, deployment, observability, capacity planning, incident response, and optimization.

Design and scale data pipelines and ML/LLM systems, build agentic automation for pipeline generation and maintenance, improve data monitoring, and collaborate with analysts, product, and ML teams to deliver reliable end-to-end data and AI infrastructure for a high-growth e-commerce platform.