Founding Product Platform Engineer Expert
Ethos • Remote
Education
Any
Type
Pay Rate
$100/task
Listed
Today
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About this Role
About the job
About this opportunity
We're helping a leading, early-stage stealth start-up building multi-agentic prediction software. Their mission is to predict human behaviour at scale. They're a small, nimble team looking for their Founding Product Platform Engineer to help lay the technical foundation for something extremely 'crazy'!
You will be instrumental in building the core product across frontend, backend, and data workflows. This means turning prototype scripts and one-off workflows into robust, reusable product systems. You'll build customer-facing interfaces for querying, exploring, and auditing AI-generated insights, and design clear product experiences for complex concepts like evidence, uncertainty, provenance, traces, predictions, and reports. On the backend, you'll build APIs for customer workspaces, data ingestion, workflow execution, auth, and artifact retrieval, and design systems for storing source files, runs, outputs, traces, reports, evaluations, and provenance. Expect to create internal tools that make customer deployments faster and less manual, and own early deployment, observability, reliability, and security foundations. You'll work closely with the Founding AI Engineer to productize AI workflows and with the founders to turn customer pain into product primitives, helping to define their engineering standards, architecture, and product culture.
Compensation: £80–100k
Commitment: Full-time
Location: London
Start date: As soon as possible
Key requirements
Proven experience building full-stack applications, with a strong grasp of both frontend and backend technologies.
Experience designing and implementing robust APIs and data storage systems.
Ability to translate complex technical concepts into intuitive user experiences.
Comfortable owning foundational engineering work, from deployment to security.
Eagerness to work in a fast-paced, early-stage startup environment and contribute to defining engineering culture.
Requirements
- Must be eligible to work in Remote
- Fluent proficiency in English (Written & Verbal)
- Reliable high-speed internet connection
- Bachelor's degree or equivalent professional experience
- Demonstrated expertise in STEM
Compensation Analysis
Shape the "brain" of future AI. By working as a Founding Product Platform Engineer Expert, you ensure that future models understand the nuance of your field. At $100/hr, it's a lucrative way to preserve the integrity of your profession in the digital age.
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Frequently Asked Questions
Is this normal AI training work?
No. Ethos is an expert network — not a task queue. You won't be rating chatbot responses. AI labs, investment funds, and Fortune 500s pay to access your specific domain knowledge: deal analysis, clinical reasoning, legal logic, financial modeling. Work takes three forms: paid consulting engagements (multi-week), 30–60 minute advisory calls, and targeted research surveys.
Do I need to constantly apply for projects?
No. Once your profile is live, Ethos's AI automatically matches you to inbound opportunities based on your career history. Companies find you — you don't hunt for listings. Your Expert Score rises with each completed engagement, which unlocks higher-value inbound over time. Ethos already works with 25+ private equity firms, hedge funds, and consultancies, so deal flow is real.
When and how do I get paid?
Payment is processed within 30 days of submitting your invoice after a project closes. This net-30 schedule is standard for enterprise expert networks but slower than weekly-paying AI platforms. Plan your cash flow accordingly — this is not a 'get paid Friday' setup.
Is this traditional consulting?
Not exactly. You act as a "Teacher" for advanced AI. Instead of client deliverables, you are given complex scenarios to evaluate. You grade the AI's logic, correct its hallucinations, and provide expert-level reasoning. Your job is to train the model to think like you do.
Why is the pay so high?
This role requires deep, verified expertise. General knowledge isn't enough; the model is specifically being trained on "edge cases"—the rare, difficult, or highly technical nuances that only a senior professional would know.
What is the workload like?
This is cognitive, deep work. Unlike simple data labeling, you might spend 45-60 minutes on a single task, researching citations or verifying complex calculations. Quality is prioritized over speed.
Who built Ethos and is it legitimate?
Ethos raised $3.5M from General Catalyst and was co-founded by Daniel Mankowitz (Google DeepMind research scientist and lead author of AlphaDev) and James Lo (McKinsey, SoftBank Vision Fund). Over 17,000 experts have signed up and it is actively working with 25+ PE firms, hedge funds, and consultancies. It is legitimate and well-funded. The referral link on this page is an affiliate link — this does not affect your pay or opportunities.