3 months ago
Remote, WorldwideMid Level
Responsibilities
- Partner with the GM and early customers to define the vertical’s technical requirements and strategy.
- Build reusable MVP patterns, integrations, tooling, workflows, and infrastructure on top of Protege’s core platform.
- Make architectural decisions about platform capabilities versus vertical-specific tooling.
- Lead initial customer engagements end-to-end, including technical scoping, delivery, and post-launch support.
- Write robust, maintainable code that addresses customer needs while becoming reusable infrastructure.
- Translate customer requirements into durable systems and create a technical playbook for future FDEs.
- Identify infrastructure gaps, repeatable use cases, and product opportunities from live engagements.
- Partner with Product and Engineering to elevate proven capabilities into the core platform.
- Collaborate with the GM or Solutions Lead, Data Lab, and other FDEs on technical strategy and shared patterns.
- Serve as the technical voice of the vertical as it grows.
Requirements
- 3+ years of engineering experience, including meaningful 0-to-1 work as a founding engineer, early technical lead, or builder in a highly ambiguous environment.
- Strong engineering generalist instincts with a backend and data orientation.
- Hands-on experience with Python and SQL.
- Comfort working across infrastructure, application logic, and data systems.
- Ability to create structure without a defined roadmap and move quickly in ambiguous environments.
- Strong technical judgment regarding short-term delivery versus long-term architecture.
- Strong written and verbal communication skills with senior technical and business stakeholders.
- Ability to independently run customer technical-scoping conversations and translate them into execution plans.
- Prior founding engineer experience at a successful startup is preferred.
- Experience extending an existing platform into a new domain or use case is preferred.
- Experience turning customer-specific work into reusable infrastructure or product capabilities is preferred.
- Familiarity with ML, NLP, or LLM-based systems is preferred.
