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

The SVP of Product Strategist defines the product roadmap and leads front-end product strategy and consumer-driven feature definition, partnering with engineering and executive teams to ensure market alignment and decision-making on initiatives.

Lead cross-functional technical projects to deliver new consumer products to market. Maintain schedules, align global teams, track technical issues in JIRA, drive meetings, support technical activities, prepare executive updates, and ensure products meet retailer requirements and quality standards.

The Principal Electrical Systems Engineer will focus on system architecture, design, and prototyping across electrical and embedded domains, collaborating with cross-functional teams to evaluate emerging technologies and inform product direction.

The Quality Engineer will analyze customer complaints, drive continuous improvement in product and process quality, collaborate cross-functionally, and ensure compliance with quality standards pre and post-launch.

The role involves leading product development from concept to market, managing team members, defining product specs, and ensuring quality, user experience, and business results while collaborating cross-functionally.

The National Account Manager will lead SharkNinja's Amazon business, driving growth and managing strategic partnerships, promotions, pricing, and assortment strategies.

The eCommerce Key Account Manager will drive Amazon sales strategies, manage relationships with Vendor Services, analyze performance, and optimize pricing and promotions to increase market share and sales.

Support product management and development for Ninja Business by assisting with new product launches, market research, and cross-functional team collaboration.

The Director of Program Management at SharkNinja will lead program managers and coordinate cross-functional teams to ensure timely product development and delivery while adopting a consumer-first approach.

Lead the design, development, and deployment of machine learning models, collaborating with teams and mentoring engineers. Focus on scalable ML workflows.