--- title: 'Forward Deployed Engineer, Video at Protege' canonical: 'https://feeny.ai/job/forward-deployed-engineer-video-protege-remote-ne5hrfq3sqtq' type: 'job' last_seen: '2026-09-11' --- # Forward Deployed Engineer, Video at Protege - **Company:** Protege - **Location:** Remote - **Employment:** full-time - **Work type:** remote - **Posted:** 2026-08-25 - **Last confirmed live:** 2026-09-11 - **Apply:** https://jobs.ashbyhq.com/protege/5b9a6b80-3957-4fcc-9583-b8c977839343 ## Job description Company Overview: 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. ## About the Role Protege is hiring an FDE to support our video vertical. This is an engineering role with two key mandates: own the technical success of our video customers, and build the reusable pipes that enable future scale. You will partner closely with the GM of the vertical, product and platform engineering, Data Lab, and commercial teams to navigate external requirements and develop solutions to execute on those requirements. Protege’s video catalog already possesses hundreds of thousands of hours of raw video, this role will be instrumental in continuing to iterate on ways we curate, process, and deliver often bespoke and highly specific datasets to our customers. This role is ideal for engineers who prioritize both constantly learning through solving difficult problems and interfacing and directly owning customer outcomes. You'll be responsible for managing customer requests, newly ingested partner datasets and architecture decisions all at the same time, often across multiple deals. The pace is fast, the ambiguity is real, and when deals are live, availability outside standard hours is part of the job. If this type of environment and ownership excites you, there could be a strong fit. ## What You'll Do Own Customer Engagements End to End - Work with the GM of the vertical, core technical teams, and commercial stakeholders from feasibility through post-delivery support. - Translate a customer's model-development goals into an executable technical plan with clear acceptance criteria. - Own the implementation and operation of the engagements you lead. Evolve the Measurement Layer - Build the tooling that turns raw footage into something we can describe and sell. Partner metadata is usually thin and inconsistent, so most of what we know about a dataset is what we measured ourselves. - Our existing catalog is far too large for any one person to watch and curate from themselves. This role will continue to expand the ways in which we respond to volume requests on new and unique data requests - Iterate on solutions for rapidly characterizing and quality checking unknown datasets to continuously expand our catalog offerings Turn Deal Work Into Product Leverage - Work in tandem with the product and core engineering teams to identify areas of growth for the platform based on customer requests and learnings from the front lines. - Identify recurring patterns that should become shared cross-vertical platform capabilities and contribute directly to designing and building them. - Build the video vertical's technical playbooks and quality standards so the function scales with every new request. What Success Looks Like 30 Days: Learn and Ship - Learn Protege's platform, our existing video catalog, active customer and partner portfolio, and current processing and delivery systems. - Pair with an engineer on a live video deal to understand what a delivery actually looks like here. - Map the largest gaps in the vertical's tooling and operating model, and propose a prioritized plan for closing them. 60 Days: Own End-to-End - Operate and run an active video deal as the primary FDE. - Build or meaningfully extend a tool or workflow that came out of a live customer request. - Establish a communication cycle with other FDEs and product to surface patterns worth generalizing. 90 Days: Operate Independently - Serve as the default technical owner across the video vertical's active portfolio, including multiple concurrent deals. - Own end-to-end architecture and delivery for video customers, including post-delivery support and iteration. - Establish the first version of the video FDE playbook and reusable toolkit. - Maintain a concrete roadmap of platform investments aimed at increasing the vertical's delivery capacity. ## What You Bring Must Haves - 3+ years of experience as an engineer, including meaningful exposure to customers or external technical stakeholders. - Experience working directly with media data, with a strong preference for video specifically. - Experience building and operating systems that process, analyze, or deliver data at scale - Customer-facing ability, including translating ambiguous requirements, communicating trade-offs, and building trust with technical stakeholders. - Demonstrated end-to-end ownership, from initial problem definition through implementation, validation, and support. - High ambiguity tolerance and bias to action, with the judgment to know when to investigate further or push back. - Comfort with the intensity and pace of a fast-moving environment, including multiple concurrent priorities and time-sensitive customer work. Nice to Haves - Hands-on experience with video processing at scale: codecs and transcoding, ffmpeg, shot detection, frame sampling strategies, or perceptual quality measurement. - Experience at an early-stage company, as a founding or early engineer, or in another startup-like environment with broad ownership. - Hands-on experience with Python and SQL. - Experience with search, vector embeddings, semantic retrieval, or ML-assisted data curation. - Experience evaluating or deploying vision-language models, including building the evaluation harness rather than just calling the model. - Product engineering experience or a strong product mindset developed in close partnership with users. - Experience with our cloud and data infrastructure (AWS, Databricks, Dagster, Vercel are the key tools). 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. ## About Protege ## Company Overview - **One-liner**: Protege is a platform for the secure exchange of proprietary, real-world data between data holders and AI developers, covering the full AI lifecycle from pre-training to evaluation. - **Entity Type**: Private (Series A; $90M total funding) - **Headquarters**: New York City, New York, United States - **Founded**: 2024 - **Founders**: Bobby Samuels (CEO), Travis May (Chairman), Engy Ziedan (Chief Scientific Officer), Richard Ho (CTO) ## Core Business - **Primary Industry**: Data Infrastructure and Analytics / AI Training Data Marketplace - **Target Customers**: B2B – AI model builders (startups to enterprises) and data holders (healthcare, media, audio, video, physical intelligence companies) - **Mission**: “Building a world where the right data powers AI for the good of humanity” – curating and connecting high-quality data with expertise while protecting and fairly compensating data holders. ## Products & Services - **Protege Platform**: A marketplace and data infrastructure that enables secure, governed exchange of proprietary datasets for AI training. - **Pre-Training Datasets**: Massive, diverse real-world datasets across industries for foundation model training. - **Post-Training & Fine-Tuning Data**: Narrower, domain-specific datasets for supervised training and human feedback. - **Evaluation & Benchmarks**: Contaminated‑free, real‑world test sets (e.g., Protege Evaluation Datasets and Benchmarks for Healthcare AI) to measure model performance. - **Data Partner Revenue Program**: Monetization channel for data holders with provenance and rights protections. ## Market Standing - **Valuation**: Not disclosed - **Key Metric**: Total funding of **$90M** across three Series A extensions (Seed: $10M led by CRV; Series A: $25M led by Andreessen Horowitz, $25M led by Footwork, $30M extension led by a16z) - **Notable Investors/Partners**: Andreessen Horowitz, CRV, Footwork; acquired Calliope Networks (Dec 2024) - **Growth Signals**: Headcount of 63 employees (+203.7% YoY); operations in 6 countries; rapid hiring (14 open positions); active expansion into healthcare, audio, video, and spatial intelligence verticals ## Competitive Advantages - **Trust & Governance**: Built‑in rights protections, provenance tracking, and security for data holders – a key differentiator in an era of IP and compliance concerns. - **Domain Expertise**: Team of experienced startup operators and scientists with deep industry knowledge (healthcare, media, etc.). - **Curation + Scale**: Combines curated, real‑world datasets with expert oversight, bridging the gap between raw data and AI‑ready training sets. - **Early Traction**: Already serving customers across multiple high‑value domains (healthcare, media, audio, motion capture). ## Strategic Focus - **Vertical Expansion**: Hiring General Managers for healthcare, video, audio, and spatial/physical intelligence to deepen domain‑specific offerings. - **Benchmarks & Evaluation**: Developing sector‑specific evaluation datasets (e.g., healthcare) to become the standard for model testing. - **Platform Growth**: Scaling the two‑sided marketplace to attract more data holders and AI builders globally. ## Why Work Here - **Remote‑First, Locally‑Connected**: Default remote with regular company‑sponsored off‑sites for collaboration and team building. - **Competitive Pay & Equity**: Premium market salaries and ownership through equity, aligning employee growth with company success. - **Comprehensive Benefits**: Full coverage for medical, dental, and vision plans for employees and dependents. - **High‑Trust Time Off**: Flexible, impact‑driven time off policy. - **Culture & Values**: Emphasis on ownership, delivering together, ethical impact, and outcome‑focused work. Team includes early employees from Datavant, Verana Health, dbt Labs, Facebook, and Mastercard. - **Growth Opportunity**: Rapidly scaling startup with clear path to leadership roles; active hiring in engineering, research, sales, and operations. ## Sources 1. [Protege Website](https://www.withprotege.ai/) 2. [LinkedIn Company Profile](https://www.linkedin.com/company/withprotege) 3. [Protege Careers Page](https://www.withprotege.ai/careers) 4. [Protege People Page](https://www.withprotege.ai/people) 5. 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