Engineering: Staff Customer Forward Deployed Engineer

Amplitude • San Francisco, CA

1d

About The Position

Amplitude is the leading AI analytics platform, and our ability to deliver measurable customer outcomes quickly is a key part of how we keep that lead. The Customer FDE (Forward Deployed Engineering) team sits at the intersection of engineering, product, and customer success — owning the technical delivery that takes validated products from co-development and implements them across enterprise customers.
As a Staff Customer Forward Deployed Engineer, you will own end-to-end technical delivery for enterprise customer implementations, from sales engagement through post-deployment validation. You'll work directly in Amplitude's product codebase, submitting PRs, shipping customer-specific solutions, and building reusable patterns that make every successive engagement faster. This is not a traditional support or solutions role. Customer FDEs are engineers first who partner closely with Sales, Customer Success, Product, and Engineering to turn customer needs into working software. The right person thrives in ambiguity, learns new domains quickly, and cares as much about the customer's outcome as about technical elegance.

Requirements

• 7+ years of experience, including a track record of owning customer-facing technical engagements end-to-end
• Demonstrated ability to architect reusable solutions and mentor other engineers
• Comfortable operating autonomously across 4–6 concurrent customer engagements
• Hands-on experience shipping software in customer-facing contexts — you've owned or significantly contributed to implementations, integrations, or technical engagements where you delivered working solutions directly to customers or stakeholders
• Comfortable working in complex codebases you didn't build — you can read, write, and review production code confidently, navigate unfamiliar systems, and submit PRs with appropriate testing and review awareness
• Fluency with data and integrations — you understand event schemas, data pipelines, APIs, SDKs, and integrations, the building blocks of analytics implementations
• Default to showing, not telling — you reach for prototypes, wireframes, demos, and visual artifacts to communicate technical solutions, not lengthy emails or slide decks
• Operate with high ownership and bias toward action — you don't wait for perfect requirements; you build something, show it, learn from the reaction, and iterate fast; you don't hand off problems, you hand off working solutions
• Communicate clearly with diverse audiences — you can move fluidly between a technical conversation about data pipelines and a business conversation about what metrics matter and why
• Relentless about getting the customer to value — you take ownership of customer outcomes and drive implementations to completion, removing blockers and finding creative paths forward
• Curious and fast-learning — you enjoy picking up new domains and applying that knowledge quickly; the fastest way to become a great engineer is to build things that real people depend on, in environments you don't control

Nice To Haves

• Familiarity with TypeScript, React, Python, Node.js, and AWS

Responsibilities

• 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
• 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
• Ship early, ship often, and gather feedback — treat every customer interaction as an opportunity to validate your approach and course-correct quickly
• 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
• 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
• Establish an AI-native engineering workflow — AI tools are integral to how you write, test, debug, and deliver code, not an occasional supplement; this is a professional standard, not an optional enhancement
• Proactively identify the right engagements — dictate what you work on, identify accounts that need FDE engagement pre-Sales, and have the judgment to say "no" when the fit isn't right
• Build cross-functional trust — partner with Sales, Customer Success, and Product Engineering as a trusted technical voice in customer conversations and internal planning
• Instrument and measure your impact — track implementation cycle time, customer outcome achievement, pattern reuse rate, and product signal quality to ensure you're shipping changes that actually move the business

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed
• Number of Employees: 251-500 employees