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

Perform digital forensics, malware analysis, and incident response for SOC operations. Collect and restore digital evidence, document investigations for legal proceedings, triage incidents, recommend countermeasures, and maintain forensic policies and processes.

Implement and maintain AWS cloud standards, IaC patterns, and CI/CD automation to enable developer self-service. Support containerized workloads, monitoring, security/compliance, troubleshooting, documentation, and participate in on-call rotation to ensure reliable, cost-efficient cloud platform operations.

Lead integrations and onboarding for newly acquired medical practices: develop transition plans, manage change, train staff, coordinate cross-functional teams, track milestones, resolve implementation issues, and mentor operations staff to drive successful Go Live and operational alignment.

Design conceptual, logical, and physical data models and data pipelines to enable analytics and BI. Collaborate with business stakeholders, data engineers, and data scientists to assess data quality, optimize batch and real-time processes, and promote data architecture best practices and governance.

Develop sales strategies to engage brokers and clients, maintain relationships, coordinate with team members, and meet revenue goals.

Work at the intersection of data analytics and manufacturing quality to transform fleet-scale test and operational data into KPIs, dashboards, and AI-enabled applications. Perform ETL and statistical analysis, build dashboards, embed AI/ML services, automate workflows, and collaborate across engineering, product, and supplier teams to improve data quality and manufacturing reliability.

Deliver virtual, structured customer training in English and Portuguese to drive onboarding and adoption of Keepers cybersecurity platform. Facilitate workshops and webinars, maintain and update training materials, support basic LMS needs, gather feedback, document sessions, provide post-training follow-up, and ensure customers adopt security best practices.

Lead enterprise sales skills training strategy—diagnose skill gaps, design and deliver instructor-led and virtual practice-based learning, create leader reinforcement toolkits, operationalize post-training reinforcement, measure effectiveness, and partner with Sales leadership to drive measurable sales outcomes.

Build and ship ML-powered SaaS features end-to-end: design data/feature pipelines, develop and deploy models (forecasting, ranking, recommendations, optimization), define evaluation/A-B testing, monitor drift, integrate models into product workflows, influence roadmap, mentor teammates, and support MLOps and cloud data infrastructure to ensure measurable product impact.

The Product Manager will drive the vision and execution of AI/ML solutions and data products, collaborating closely with customers and cross-functional teams to deliver impactful solutions and measure product success.

Embed with a core business area to define problems, set metrics, run analyses and experiments, build reports, and surface actionable insights. Drive outcomes by recommending and implementing data-driven decisions across growth, product, AI/automation, or partnerships, and communicate findings to stakeholders and leadership.

Embedded within a core business area, you will define analytical problems, build metrics and reports, run analyses and experiments, surface insights, and drive data-driven recommendations end-to-end to influence product, growth, AI, or partnerships.

Embed within a core business area to own analytics end-to-end: define problems, build metrics/reports/experiments, analyze data, surface insights, and drive outcome-focused recommendations with stakeholders to improve growth, product, AI/automation, or partnerships.

Design, develop, and deploy secure, scalable software solutions; implement and automate CI/CD pipelines and testing; manage cloud infrastructure (AWS/Azure) and infrastructure automation; provide Tier III support, monitor performance and SLAs, and train teams on automation best practices.

Design, build, and maintain AI-powered applications and services focused on agentic AI and LLM workflows. Work includes model training, fine-tuning, evaluation, serving, data pipelines, testing, cloud deployment (AWS preferred), and collaborating with cross-functional teams to productionize scalable, secure, and performant AI solutions.

Build Nuclearn's RevOps function: own HubSpot as single source of truth, design forecasting and pipeline analytics, create revenue metrics and dashboards, tighten quote-to-cash handoffs, and define GTM processes and enablement to scale Sales, Customer Outcomes, Marketing, and Finance.

Deploy, configure, and integrate Nuclearn's AI platform on customer infrastructure (on‑prem/air‑gapped or cloud). Drive adoption through training and troubleshooting, act as technical advisor to plant engineers and IT, surface customer feedback to Product and Engineering, and own post‑go‑live relationships toward expansion.