GrowthBook

Job Description

We’re a Series A startup with a fast-growing user base and a small, passionate team. We're looking for our first Solutions Engineer to help scale our go-to-market efforts and support our technical customers through every phase of the journey, from pre-sales to post-sales integration and onboarding.

What You’ll Do

You will partner with an Account Executive during pre-sales to scope solutions, answer technical questions, and lead product demos for technical audiences.

You will also act as a trusted technical advisor during onboarding and post-sale implementation. Here are some examples of things you might help customers with:

We’re open source and some customers want to self-host the platform. They may need architecture recommendations and general infrastructure help. This includes integrating with their identity provider and observability tools.
We have SDKs for back-end, front-end, mobile, and edge. It’s not always clear which one a customer should use (e.g. should they add us to their mobile app directly or proxy through a back-end service?). They may also have specific questions around caching strategies, performance, and fault tolerance.
We are warehouse native and connect to our customer’s existing data (Snowflake, BigQuery, Databricks, etc.). They may have questions around db schema design, security, and performance/cost optimization.

You will also serve as the voice of the customer, translating feedback into product improvements in collaboration with engineering and design. This may also involve contributing to our docs or building sample apps.

Requirements

Extensive experience in the modern JavaScript ecosystem (Typescript, React, Node.js)
Some experience with at least one other language (Python, Go, Java, etc.)
Some experience with SQL databases
Fluent English and excellent communication skills
Startup experience or interest working in a small company
Bonus: Contributed to an open-source project
Bonus: Used feature flags or A/B testing at a previous company
Bonus: Worked with data-heavy analytics applications