Product Marketing Manager – AI at Canonical

Job Description

We deliver open source to the world faster, more securely and more cost effectively than any other company. If you’re interested in a career at Canonical, we are a remote-first company so please apply to any suitable role as skills are valued more than location, despite some having a preferred geographic preference.

What your day will look like

Be responsible for go-to-market planning and execution for Canonical’s range of MLOps and data products Lead on content dissemination, campaign development and planning for product launches. You will lead on the development of compelling messaging and positioning that emphasizes business value and connects with target audiences throughout the buying journey Conceiving and executing customer base communications and marketing programs to upsell and cross sell into our large base of customers Collaborating with demand generation teams, utilizing data and insights to create and improve strategies that drive traffic to our content, optimizing marketing funnels Work with other teams to plan event, webinars and support paid and social media promotion Create and execute content strategies that drive product interest and adoption with relevant target audiences Monitoring the competitive landscape to define product positioning that differentiates

What we are looking for in you

Experience in a product marketing function for enterprise IT products (SaaS experience preferred) Passion for the AI and data marketing Strong inter-personal management skills. Proven analytical skills, able to assess opportunities and make decisions on ROI/advantages of programs & investments. Appetite to deliver strong results and innovation. Growth mindset – someone who is not afraid to think big and take on risk. Willingness to roll up their sleeves. Exceptional verbal and written communication skills. Ability to work and thrive in a self-starter, fast-paced and changing environment Love for diverse work assignments and the opportunity to try new approaches