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Clera

GTM Engineer

San Francisco$120k–$250kfulltimemidAdded yesterday

About this role

An early-stage open-source MLOps company seeks a GTM Engineer to build and scale the SF AI infrastructure community from scratch. You'll own developer events, represent the company at conferences, evangelize the Python-based platform to ML engineers, and instrument community signals into a measurable pipeline—reporting directly to founders.

What you'll do

  • Launch and host a regular SF developer meetup series targeting the ML infrastructure community
  • Represent the company at Bay Area AI/ML conferences, hackathons, and technical events
  • Demo the Python-based open-source framework live to technical audiences and answer engineering questions
  • Create and distribute technical content including blog posts, demo videos, and social media
  • Integrate community signals (GitHub, Mixpanel, CRM, Clay) into an automated GTM workflow with enrichment and scoring
  • Surface market intelligence on emerging tools, pain points, and buying signals to inform product and GTM strategy

What they're looking for

  • Developer relations and community building
  • Event hosting and conference speaking
  • Python framework knowledge and technical demoing
  • CRM and data enrichment tools (Clay, Mixpanel)
  • API integration and workflow automation
  • Technical content creation and writing
  • Product analytics and pipeline tracking
  • Open-source community experience

Benefits

  • Salary $120,000–$250,000 annually
  • Direct access to founders with strategic ownership of US GTM
  • Build a category-defining community in a top AI infrastructure market
  • High autonomy in an early-stage startup environment
  • Meaningful visibility and influence on company direction
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Clera

Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.

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Likely interview questions

  • Tell us about a developer community or event series you built from zero—how did you measure success and convert engagement into business outcomes?
  • How would you approach demoing a Python-based MLOps framework to an audience of skeptical ML engineers, and how would you handle tough technical questions?
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