Senior AI Solutions Builder
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Some ghost-posting signals
- open for 87 days (60–89 days is elevated risk)
- 31 open roles at this company in 30 days (mass-hiring blitz)
- no salary disclosed (correlates with ghost postings)
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About the role
You Will
Design and ship AI-powered copilots, agents, and decision-support tools for the Product team, starting with Pricing
Build data pipelines and analytical models for pricing intelligence
Develop autonomous agents that automate recurring Product tasks
Automate manual workflows across product tools so the right action happens when a signal fires
Build LLM-based scoring models that give roadmap and prioritization decisions a data backbone
Enable and upskill product teams through AI playbooks, sessions, and hands-on co-building
Collaborate with builders across Engineering, CS, GTM, and other teams to co-create solutions that scale
Define and track impact: time-to-insight, decision velocity, manual hours eliminated, and business outcomes
You Bring
Proven, hands-on experience building and shipping AI-powered tools, agents, or pipelines in production environments
Builder / vibe coder mindset — uses AI-assisted tools (Claude, Cursor, Copilot, n8n) to ship independently without an engineering ticket
Strong analytical foundation: pricing or business scenario modeling, experimentation design, usage data analysis
Proficiency in Python and SQL; comfortable with LLM APIs, prompt engineering, and agentic frameworks
Experience working cross-functionally with Product, Finance, and go-to-market teams in a B2B SaaS environment
Ability to connect systems independently: APIs, webhooks, data pipelines
Strong communication and collaboration skills across diverse teams
Ability to prioritize, problem-solve, and navigate ambiguity in a dynamic environment
Comfortable learning and applying new technologies, tools, and methodologies
5+ years in AI/ML engineering, product analytics, or a closely related builder role
Ideally, You Bring
Experience in pricing, monetization, revenue analytics, or usage-based commercial models
Background in Product work
Familiarity with causal inference, A/B experimentation, or uplift modeling
Comfortable with analytics platforms (Heap, GA4, Mixpanel, Amplitude) and PM tools (Jira, Confluence, Productboard, etc.)
Experience working in a distributed, multicultural environment
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