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CleraPosted 1 week ago
EXPIRED

Pricing Architect

$180,000–$220,000 year

Remote

Full TimeStartup

Job Summary

Own end-to-end pricing engagements from discovery workshops through live model delivery and post-go-live optimisation. Design segmentation, packaging, price metrics, and monetisation logic tailored to each customer's business while leading independent market research and C-level stakeholder workshops. Act as a trusted pricing advisor to set expectations, align on value, and drive expansion opportunities into upsells. Use the AI pricing platform daily to solve real customer problems and provide continuous product feedback to sharpen the pricing engine. Partner with product and engineering to support rollout, change management, and sales team onboarding. Document learnings to build a repeatable, scalable methodology. Participate in sales pitches to identify and qualify prospects. This high-ownership role at an early-stage company helps build the playbook that scales the AI-native pricing platform for B2B SaaS.

Required Qualifications

  • 5–7+ years in pricing, commercial strategy, or revenue management
  • background in Tier-1 strategy consulting
  • pricing/monetisation roles in tech or SaaS
  • Deep expertise in pricing fundamentals: segmentation, packaging, price metrics, discounting, and willingness-to-pay methodologies
  • Proven track record of leading end-to-end pricing engagements from concept to live model
  • full ownership of multiple engagements
  • Hands-on use of GenAI/LLM tools in day-to-day pricing work today
  • Proficiency with data analysis using spreadsheets and SQL
  • Excellent communication and presentation skills
  • ability to influence C-level and cross-functional stakeholders
  • Professional fluency in English
  • This is an on-site role based in Amsterdam, Netherlands
  • Candidates must be based in Amsterdam or willing to relocate

Desired Qualifications

  • Experience coaching or mentoring others in pricing or related commercial functions
  • Demonstrated comfort thriving in fast-paced, high-ambiguity startup environments

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