Deployed AI Product Strategist

JFrog•Sunnyvale, CA

About The Position

JFrog is hiring a Deployed AI Product Strategist embedded in the San Francisco AI ecosystem. The role treats the broader SF AI community as its customer and turns intelligence gathered from that ecosystem into input for JFrog’s product, strategy, and roadmap. The strategist works directly under the CTO and represents JFrog as a peer in the community. The position combines ecosystem scouting, technical evaluation, product strategy, relationship-building, and internal knowledge-sharing. The strategist will track emerging AI tools and architectural patterns, identify enterprise-ready vendors and opportunities, prototype new APIs and frameworks, and communicate useful findings to executive and cross-functional stakeholders. The role partners with Product, Engineering, and GTM teams to inform platform direction and competitive positioning.

Requirements

At least 7 years of experience in a technical or product engineering role, such as FDE, Field Engineering, DevRel, or ML.
Firsthand experience building with LLMs, RAG pipelines, and agentic frameworks.
Deep involvement in the San Francisco AI ecosystem, with an active network and public technical presence, such as a blog, Substack newsletter, X-feed, or open-source contributions.
Ability to listen empathetically and distill high-volume, complex ecosystem signals into clear, actionable insights.
Ability to evaluate architectural tradeoffs quickly and stress-test developer tools to assess their platform utility.

Responsibilities

Build a structured view of emerging AI vendors and startups, including which are enterprise-ready or overhyped, and deliver actionable signal briefs to executive stakeholders.
Track emerging AI tools, frameworks, and architectural patterns ahead of mainstream adoption to anticipate shifts and inform the product roadmap.
Cultivate peer-to-peer relationships with AI enthusiasts, founders, and enterprise practitioners, building credibility in local AI and developer communities.
Map active builders, emerging workflows, and problem-solving trends to uncover product insights and strategic opportunities, maintaining a living knowledge base.
Prototype and assess new APIs, tools, and agentic frameworks, producing concise technical evaluations of their utility, limitations, and strategic relevance.
Partner with technical stakeholders and drive high-level discussion of LLMs, RAG architectures, fine-tuning, training, and agentic infrastructure to guide product direction.
Connect the external AI ecosystem with JFrog’s internal teams, partnering with Product, Engineering, and GTM to refine the platform roadmap and competitive positioning.
Lead regular technical briefing sessions on emerging AI trends to amplify knowledge and alignment within the organization.