
Forward Deployed Engineer, New Verticals
Protege · United States
- Hybrid
- Full-time
- $150,000 / year
- United States
Job highlights
- Build new AI data vertical from scratch.
- Define market, strategy, and technical capabilities.
- Develop reusable infrastructure and technical patterns.
- Lead customer engagements from start to finish.
- Shape product roadmap with customer insights.
About the role
About Protege
We are building Protege to solve the biggest unmet need in AI — getting access to the right training data. The process today is time intensive, incredibly expensive, and often ends in failure. The Protege platform facilitates the secure, efficient, and privacy-centric exchange of AI training data.
Solving AI’s data problem is a generational opportunity. We’re backed by world-class investors and already powering partnerships with some of the most ambitious teams in AI. The company that succeeds will be one of the largest in AI — and in tech.
We’re a lean, fast-moving, high-trust team of builders who are obsessed with velocity and impact. Our culture is built for people who thrive on ambiguity, own outcomes, and want to shape the future of data and AI.
Role Overview
We’re hiring a founding Forward Deployed Engineer to help build a new vertical from the ground up. You’ll be the first FDE dedicated to this vertical, working directly with the GM to define the market, strategy, and early commercial motion. Your job is to turn early customer demand into durable technical capability: defining what the vertical needs, building reusable infrastructure on top of our existing platform, and establishing the technical patterns that future engagements and future hires can build on.
This is not a standard implementation role. It sits at the intersection of engineering, product judgment, and customer reality. You should be excited to work from first principles, operate in ambiguity, iterate quickly, and partner with product engineering to make strong calls about what should become a core platform capability versus what should remain vertical-specific.
What You'll Do
Build the Technical Foundation
- Partner with the GM and early customers to define what the vertical actually needs technically.
- Build the first MVP of reusable patterns, integrations, and tooling that future engagements will run on, leveraging our core platform where it fits and extending it where the vertical requires something new.
- Make architectural decisions about what belongs in the platform layer versus vertical-specific tooling.
- Create the initial technical playbook so future FDEs can build on a real foundation rather than starting from scratch.
Own First Deals End-to-End
- Lead the first customer engagements in the vertical, from technical scoping through delivery and post-launch support.
- Write robust code that solves immediate customer problems while compounding into reusable infrastructure.
- Navigate real-world complexity across customer data, integrations, workflows, and stakeholder dynamics.
- Translate messy customer requirements into systems that are durable and maintainable.
Shape What Becomes Product
- Partner with Product and Engineering to identify which patterns from early customer work should become core platform capabilities.
- Surface repeatable use cases, infrastructure gaps, and product opportunities from live engagements.
- Help determine when the vertical is ready to evolve from bespoke delivery into a repeatable product motion.
Partner Across The Company
- Work directly with the GM or Solutions Lead to define the vertical’s technical strategy and commercial approach.
- Partner with Data Lab on domain-specific data and research questions.
- Collaborate with other FDEs on shared patterns, tools, and approaches that should compound across verticals.
- Serve as the technical voice of the vertical as it grows.
What Success Looks Like
The shape of this role depends on the vertical you're deployed into, so we measure success based on trajectory rather than a fixed set of outputs. In the first 90 days, we expect the following to happen:
- Build an understanding of the vertical and strategy: Develop a strong understanding of the vertical, the market dynamics, and the GM's strategy for building and scaling the business. Gain context on the customer landscape, commercial motion, and the unique technical requirements that will shape the vertical's success.
- Understand customer and platform needs: Build a deep understanding of what customers and data partners need, what Protege's platform can already support, and where meaningful gaps exist. Develop a clear point of view on which constraints are temporary, which require new infrastructure, and which represent opportunities for future product investment.
- Identify the highest-leverage technical bets: Evaluate the technical landscape and identify the most important investments that will unlock customer success, accelerate delivery, and create long-term leverage for the vertical. Prioritize decisions thoughtfully, balancing immediate customer needs against durable architecture.
- Ship the first version of the vertical's infrastructure: Build the initial technical foundation for the vertical by leveraging the core platform where it fits and extending it where the vertical requires new capabilities. Deliver production-grade systems, integrations, workflows, and tooling that create a foundation future engagements can build upon.
- Lead customer engagements end-to-end: Own early customer engagements from technical scoping through delivery and post-launch support. Use learnings from those engagements to continuously improve the underlying infrastructure, implementation patterns, and technical playbook.
- Create reuse and drive productization: Successfully reuse the vertical's technical foundation across multiple customer engagements, demonstrating that the systems being built are durable rather than one-off solutions. Surface repeatable patterns, infrastructure gaps, and product opportunities, and partner with Product and Engineering to elevate proven capabilities into the core platform.
What You Bring
Must Haves
- 3+ years of engineering experience, including meaningful 0→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 where none exists and move quickly without a fully defined roadmap.
- Strong technical judgment, especially around short-term delivery versus long-term architecture.
- Strong written and verbal communication skills, including the ability to work directly with senior technical and business stakeholders.
- Ability to independently run technical scoping conversations with customers and translate them into concrete execution plans.
Nice to Haves
- Prior founding engineer experience at a successful startup.
- Experience extending an existing platform into a new domain or use case.
- Track record of turning customer-specific work into reusable internal infrastructure or product capabilities.
- Familiarity with ML, NLP, or LLM-based systems.
Why This Role Is Special
This is a rare opportunity to define the technical foundation of a new business line inside a company that already has a real platform, real customers, and real momentum.
You won’t just be executing against a spec. You’ll help decide what the spec should be. If you enjoy building in ambiguity, working directly with customers, and creating systems that become the basis for an entire vertical, this role is for you.
Protege Values
- Pass the Loved Ones’ Test: We act with integrity and do the right thing — especially when it’s hard and no one is watching.
- Always Find a Way: We are resourceful, resilient builders who solve hard problems and push through obstacles.
- Go Fast and Grow Fast: Velocity matters. We move with urgency, learn quickly, and continuously improve as individuals and as a company.
- Practice Kindness and Candor: We communicate directly and respectfully, building trust through honest feedback and genuine care for one another.
- Deliver Together: We win as one team. Collaboration, accountability, and shared ownership drive our success.
- Own the Outcome. Hone the Craft.: We take pride in our work, sweat the details, and continuously raise the bar for excellence.
Key skills/competency
- Forward Deployed Engineer
- AI Training Data
- Platform Development
- Customer Engagement
- Technical Strategy
- Python
- SQL
- Infrastructure Building
- Product Development
- ML/NLP/LLM
Skills & topics
- Forward Deployed Engineer
- AI
- Data
- Training Data
- Python
- SQL
- Engineering
- Platform
- Infrastructure
- Customer Engagement
How to get hired
- Tailor your resume: Highlight 3+ years of engineering experience, especially 0→1 work, Python, and SQL. Emphasize ambiguity navigation and technical judgment.
- Showcase your impact: Quantify achievements in previous roles, focusing on building, problem-solving, and customer interaction.
- Prepare for ambiguity: Be ready to discuss how you create structure and drive outcomes in uncertain environments.
- Demonstrate technical depth: Be prepared to discuss your experience with backend, data systems, infrastructure, and application logic.
- Research Protege's values: Align your communication and examples with their values of integrity, resourcefulness, velocity, kindness, collaboration, and ownership.
Technical preparation
Behavioral questions
Frequently asked questions
- What does a Forward Deployed Engineer at Protege do in the first 90 days?
- In the first 90 days as a Forward Deployed Engineer at Protege, you'll focus on building a deep understanding of the vertical, market dynamics, and customer needs. You'll identify key technical bets, begin shipping the initial infrastructure for the vertical, lead early customer engagements, and start creating reusable patterns that drive productization. The role emphasizes trajectory and impact over fixed outputs.
- What is the expected experience for a Forward Deployed Engineer at Protege?
- Protege seeks candidates with at least 3 years of engineering experience, including significant 0→1 work as a founding engineer or early technical lead. Essential skills include strong backend and data orientation, hands-on Python and SQL experience, comfort with infrastructure and data systems, and the ability to create structure in ambiguous environments. Prior founding experience or ML/NLP familiarity is a plus.
- How does Protege's culture support Forward Deployed Engineers?
- Protege fosters a high-trust culture for builders obsessed with velocity and impact. They value individuals who thrive in ambiguity, own outcomes, and are passionate about shaping the future of data and AI. Their core values include integrity, resourcefulness, speed, kindness, collaboration, and a commitment to owning outcomes and honing craft.
- What makes the Forward Deployed Engineer role at Protege unique?
- This role is unique because it offers the opportunity to define the technical foundation of a new business line within an established company that already has a platform, customers, and momentum. You won't just execute a spec; you'll help define it. It's ideal for those who enjoy building in ambiguity, working directly with customers, and creating systems that form the bedrock of an entire vertical.
- What kind of technical challenges will a Forward Deployed Engineer at Protege face?
- You will face challenges in defining technical needs from scratch for a new vertical, building reusable infrastructure on top of an existing platform, and making architectural decisions about platform versus vertical-specific tooling. You'll also navigate complex customer data, integrations, and workflows, translating messy requirements into durable, maintainable systems.
- How does this role contribute to Protege's overall mission?
- As a Forward Deployed Engineer, you are instrumental in solving AI's critical data problem by building out new verticals. You'll turn customer demand into tangible technical capabilities, establishing the foundational infrastructure and patterns that enable the secure, efficient, and privacy-centric exchange of AI training data, directly contributing to Protege's goal of becoming a leader in AI.