Engineering: Staff Customer Forward Deployed Engineer

Amplitude Amplitude · Data AI · San Francisco, CA · Engineering : FDE

Staff Customer Forward Deployed Engineer for an AI analytics platform, responsible for end-to-end technical delivery of enterprise customer implementations, including sales engagement, shipping customer-specific solutions, building reusable patterns, and establishing an AI-native engineering workflow. This role involves working directly in the product codebase, submitting PRs, and translating customer needs into working software.

What you'd actually do

  1. Own enterprise implementations end-to-end — engage during sales to map customer needs to capabilities, scope implementation plans, and deliver through post-deployment validation with measurable customer outcomes
  2. Work directly in the product codebase — submit PRs, test, and ship customer-specific solutions without requiring constant oversight; over time, the gap between "what we built" and "what the customer needs" keeps shrinking because you're the one closing it
  3. Ship early, ship often, and gather feedback — treat every customer interaction as an opportunity to validate your approach and course-correct quickly
  4. Build reusable patterns and playbooks — when you solve something once, make sure the next person doesn't have to solve it again; identify and document implementation patterns that reduce effort for subsequent engagements
  5. Feed structured signals back to Product — translate customer pain into actionable product feedback that influences the roadmap; surface gaps so they get fixed rather than hiding them

Skills

Required

  • 7+ years of experience
  • track record of owning customer-facing technical engagements end-to-end
  • architect reusable solutions
  • mentor other engineers
  • operating autonomously across 4–6 concurrent customer engagements
  • shipping software in customer-facing contexts
  • read, write, and review production code confidently
  • navigate unfamiliar systems
  • fluency with data and integrations
  • event schemas
  • data pipelines
  • APIs
  • SDKs
  • integrations
  • high ownership
  • bias toward action
  • communicate clearly with diverse audiences
  • relentless about getting the customer to value
  • curious and fast-learning

What the JD emphasized

  • customer-specific solutions
  • reusable patterns
  • AI-native engineering workflow
  • customer outcomes

Other signals

  • AI Agents embedded across platform
  • AI analytics platform
  • customer-specific solutions
  • reusable patterns
  • AI-native engineering workflow