Responsibilities

• Translate AI native development infrastructure pain points into competitive advantages: Transform Anaconda’s core distribution capabilities (conda, channels, packaging, models) and native AI developer tooling into compelling messaging that addresses the most critical workflow blockers for both data scientists and AI builders—complex dependency management across Python and AI stacks, inconsistent and non-reproducible environments from local to shared and production contexts, and inefficient compute and memory utilization that constrains experimentation, scaling, and iteration speed.
• Own persona-driven value propositions for the data science expansion opportunity: Develop differentiated messaging frameworks that position Anaconda as the foundational AI-native development platform that eliminates setup friction for data scientists, enabling them to focus on insights rather than infrastructure battles. Create specialized value propositions for regulated industries (financial services, healthcare, manufacturing) that emphasize security scanning, compliance management, and trusted package provenance—transforming open source governance from a barrier into a competitive advantage for enterprise AI initiatives
• Create compelling narratives around Anaconda’s AI transformation: Craft messaging that captures how Anaconda enables data science practitioners to capitalize on AI-driven opportunities by providing reliable, optimized Python environments that scale from experimentation to production
• Develop and execute comprehensive go-to-market strategies including launch planning, market positioning, and post-launch growth initiatives in partnership with Product Management and Engineering
• Serve as the expert on data science practitioners and developers:
• Leverage Python and AI/ML development expertise to ensure technical accuracy in all messaging and content, speaking authentically to practitioner audiences across traditional ML, LLM/agent workflows, and emerging AI development patterns with credible technical depth
• Establish continuous feedback loops with data scientists, ML engineers, and AI practitioners through beta programs, user interviews, and community engagement to inform product direction and refine messaging based on real-world usage patterns across the full AI/ML development lifecycle
• Partner with technical teams across the organization to communicate feature launches with appropriate technical depth and practitioner-focused value propositions that resonate with needs spanning experimentation, model deployment, MLOps, and AI governance requirements
• Become the internal authority on end-to-end AI/ML workflows, including traditional data science pipelines, LLM/agent development patterns, model deployment challenges, MLOps toolchains, competitive OSS alternatives, and evolving
• Open Source Community Leadership:

Requirements

• 3-6+ years in product marketing, developer advocacy, product management, or software engineering (with interest in pivoting to product marketing)
• Experience launching or working with open-source or developer tools, or AI products with both community adoption and commercial monetization strategies
• Strong grasp of software distribution, SDLC, DevOps practices, and AI/ML concepts
• Deep understanding of open source community culture and experience working within OSS-first organizations that have developed commercial offerings
• Exceptional technical writing skills and ability to authentically engage developer communities while advancing business objectives
• Regularly leverage AI tools to accelerate messaging & persona development, campaign analysis, and competitive intelligence.
• Growth mindset with experience leveraging AI tools, cross-functional collaboration, and startup environments
• You embody our values of Clarity, Care and Candor
• You care deeply about fostering an environment where people of all backgrounds and experiences can flourish

Preferred

• Python and/or SFDC lifecycle proficiency with deep understanding of development workflows, packaging, and ecosystem dynamics
• Comfortable with ambiguity and rapid iteration in dynamic environments
• Ability to balance strategic thinking with hands-on tactical execution
• Proficiency in leveraging gen-AI tools for workflow efficiency (ChatGPT, Claude, others)
• Experience working in a fast-paced startup environment
• Experience working in an open-source, AI, or data science-oriented company

Benefits

• Flexible Vacation Policy
• Medical, Dental, and Vision Insurance
• Short Term and Long Term Disability
• Paid Parental Leave
• Monthly Wellness Stipend
• Employee Assistance Program and Mental Health Resources