---
title: 'Member of Technical Staff (Applied AI) at Aptura'
canonical: 'https://feeny.ai/job/member-of-technical-staff-applied-ai-aptura-london-p9cz2k4q4nkd'
type: 'job'
last_seen: '2026-10-18'
---

# Member of Technical Staff (Applied AI) at Aptura

- **Company:** Aptura
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-07-22
- **Last confirmed live:** 2026-10-18
- **Apply:** https://jobs.ashbyhq.com/aptura/c299e1f2-cdb4-4842-b5f3-8aa6e57482e0/application

**Skills:** LLMs, Prompting, Agentic harnesses, RL environments, Verification logic, Reward functions, Finance domain knowledge, Healthcare domain knowledge, Legal domain knowledge, RL concepts, Model training, Post-training workflows, AWS, GCP

> Build RL environments and evaluation datasets for AI agents in finance, healthcare, and legal domains. Collaborate with domain experts to design tasks, verification logic, and reward functions while prototyping new approaches to measurement.

## Job description

## About Aptura

We build the evaluation datasets and RL environments that make AI reliable in domains where mistakes are expensive: finance, healthcare, and legal. Our team designs expert-curated training data, calibrated rubrics, and verifiable task environments for AI labs and startups pushing the frontier of what models can do in regulated industries. We're a small, lean, London based team that moves fast and takes the work seriously. Everyone contributes directly. Initiative is rewarded, and ownership is the default. If you want to shape how frontier AI learns to operate in the real world, we'd like to hear from you.

## About the Role

As a Member of Technical Staff on our Applied AI team, you will build the tasks and environments that AI labs use to train and evaluate their agents in finance, healthcare, and legal. Day to day, that looks like: constructing RL environments around spreadsheets, documents, and professional workflows. Writing verification logic and reward functions. Working with domain experts to scope what a correct answer actually looks like in an LBO model or a clinical note. Some days it's engineering, some days it's closer to research. The common thread is that you're producing the ground truth that frontier models get measured against.

## What You'll Do

- Build RL environments across finance, healthcare, and legal domains
- Assist in designing tasks with golden answers, calibrated rubrics, and programmatic reward signals
- Write verification logic and reward functions that can distinguish good model outputs from bad ones
- Work directly with domain experts (investment analysts, physicians, attorneys) to translate complex professional workflows into structured tasks
- Prototype new approaches to evaluation, verification, and synthetic data generation

Who We're Looking For

- Practical experience building with LLMs: prompting, evaluation, and agentic harnesses. You've built things that actually run, not just notebooks.
- High agency and technically sharp. You don't wait for permission, specs, or a roadmap. You see what needs doing, figure out how, and get it done.
- Comfortable working across very different contexts. The job moves between engineering, evaluation design, and deep collaboration with domain experts often in the same day.
- You ship and iterate. Small team, no room for work that sits in review. Bias toward getting something working, learning from it, and improving it.
- You own problems end to end, from scoping with a domain expert through to a working environment. If you prefer clearly partitioned tickets, this probably isn't the right fit.
- Already using LLMs as part of how you build, not just as the thing you're building for.

## Nice to Have

- Domain knowledge in finance, healthcare, or legal
- Familiarity with RL concepts, model training, and post-training workflows
- Cloud infrastructure experience (AWS or GCP)
- Previous startup experience, especially as an early engineer

## About Aptura

## Company Overview
- **One-liner**: Aptura helps train and evaluate AI to master real-world tasks in finance, healthcare, and legal sectors, specializing in reliable AI for regulated industries.
- **Entity Type**: Private (Privately Held)
- **Headquarters**: London, England, UK
- **Founded**: 2025 (incorporated 10 April 2025)
- **Founders**: Founded by ex-Lazard and Partners Group professionals (specific names not publicly disclosed)

## Core Business
- **Primary industries**: AI training and evaluation, Data services, Technology/Internet
- **Target customers**: Frontier AI labs, AI research organizations, and enterprises deploying AI in regulated industries (finance, healthcare, legal)
- **Mission/Purpose**: To bring institutional expertise from finance, healthcare, and law directly into AI model development, enabling reliable AI deployment in regulated environments

## Products & Services
- **RL Environments**: Real-world, rich environments loaded with finance, medical, and legal data, designed for verifiable rewards, custom tooling, and data licensing support. Agents complete tasks in finance spreadsheets, medical records, and legal documents with measurable outcomes.
- **Curated Datasets**: Domain-specific high-quality data (medical imaging, financial models, legal contracts) structured for training and evaluation with domain nuance.
- **Domain Expertise Services**: Internal team of physicians, attorneys, and investment analysts (with years of high-stakes experience) who work directly with AI researchers to scope and deliver projects, supported by a platform built for structured, high-quality data collection at scale.
- **Verifiable Task Design**: Combining expert knowledge, curated datasets, engineering, and real-world tasks to create training grounds for agentic AI.

## Market Standing
- **Funding**: Not publicly disclosed (company is private and early-stage)
- **Key Metric**: Total employees of 26 (as of latest LinkedIn data)
- **Notable Investors/Partners**: Works with "leading foundational AI labs" (names not publicly specified)
- **Growth Signals**: 6,160 LinkedIn followers, active job postings across multiple domains (investment banking, radiology, legal, insurance), speaking engagements at industry events (e.g., Project A discussion on reinforcement learning)

## Competitive Advantages
- **Domain-specific expertise**: Employs actual practitioners (physicians, attorneys, investment analysts) rather than generalist data labelers, enabling nuanced data and task design for regulated fields
- **Focus on verifiable, measurable outcomes**: Uses real-world tasks with objective correctness (e.g., DCF models, dental scan interpretation, contract clause analysis) rather than subjective labeling
- **Close collaboration with AI labs**: Works directly with frontier model developers, iterating rapidly on data and evaluation
- **Regulated industry specialization**: Addresses a critical gap where general-purpose AI training data fails to meet the complexity and standards of finance, healthcare, and legal applications

## Strategic Focus
- **Current priorities**: Building the infrastructure to bring institutional expertise (finance, legal, healthcare) into AI model training and evaluation at scale
- **Direction**: Expanding from frontier labs to frontline deployment of reliable AI in regulated industries; recruiting domain experts across multiple sectors (investment banking, radiology, insurance, legal) on a part-time/flexible basis
- **Partnership/event activity**: Active in the RL and AI research community, with CTO Armin Schöpf speaking at Project A on reinforcement learning

## Why Work Here
- **Culture**: Mission-driven focus on building reliable AI for high-stakes domains; emphasis on domain expertise and real-world impact
- **Remote/Hybrid Policy**: Fully remote positions available (e.g., "Fully remote, part-time, and flexible" for expert roles; Investment Banking Associate roles listed as "Remote"); also has offices in London and San Francisco
- **Compensation**: Competitive hourly rates ($80–$200/hour for expert contractor roles) with monthly retainer structures for ongoing engagements
- **Work style**: Project-based and flexible engagements, targeting professionals who want to apply their domain expertise to cutting-edge AI development
- **Team**: Small (~26 employees) but includes highly specialized domain experts and AI researchers; likely high ownership and impact per person

## Sources
1. [aptura.ai](https://www.aptura.ai/)
2. [LinkedIn - Aptura](https://www.linkedin.com/company/apturaai)
3. [Jobs.ashbyhq.com - Aptura Careers](https://jobs.ashbyhq.com/aptura)
4. [GOV.UK - APTURA AI UK LTD](https://find-and-update.company-information.service.gov.uk/company/16378696)
5. [Jobs.ashbyhq.com - Policy Expert Role](https://jobs.ashbyhq.com/aptura/a82217bb-d20e-49fa-9b19-1d0e86a664ba)

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