---
title: 'Senior Software Engineer - Paris at H Company'
canonical: 'https://feeny.ai/job/senior-software-engineer-paris-h-company-paris-bmgqvr486154'
type: 'job'
last_seen: '2026-10-17'
---

# Senior Software Engineer - Paris at H Company

- **Company:** H Company
- **Location:** Paris, France
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-10-02
- **Last confirmed live:** 2026-10-17
- **Apply:** https://jobs.ashbyhq.com/hcompany/3ba24410-c856-439e-8551-b361c8fa819e

## Job description

About H: When we released [Holo4](https://hcompany.ai/newsroom/holo4) on 28 September, we published every trajectory behind its public benchmark scores at [trajectories.hcompany.ai](http://trajectories.hcompany.ai). For OSWorld that's 369 desktop tasks, each run 3 times, with the steps, tokens and time of every attempt. This role builds and runs the evaluation framework that produces runs like these. H builds computer-use agents and the models behind them. Developers use them through a [managed API](https://hcompany.ai/newsroom/computer-use-agents-api), and our forward deployed engineers take them into enterprise workflows.

What this team owns The evaluation framework: orchestration, runtimes and observability. Researchers and forward deployed engineers bring the benchmarks, across web apps, desktop applications and the command line. Your job is to make the framework that runs them reliable, fast and cheap, and to make adding a new one quick. Research uses the results to choose checkpoints and decide whether a model ships. Product and the forward deployed engineers use them to measure agents on customer workflows. It carries roughly 50 benchmarks now. That number should be between 100 and 200 soon, and the framework has to keep up.

## What you'd be doing

- Integration support for researchers and forward deployed engineers bringing in a benchmark, with a shorter path each time.
- Setting the standard for how a benchmark enters the framework, and building the checks that enforce it.
- Scheduling and observability, so cluster capacity isn't left idle while evaluation jobs queue.
- Reproducible results across trials, so a release decision rests on numbers that hold.
- Whatever stack a benchmark calls for. One week that's cluster tuning; the next it's a browser extension or desktop environments.
- Time with customers, from single developers to large companies, to find out what they want measured, then automating it so the results flow back into our harnesses and models.

The first few months By 3 months you'll have helped researchers or forward deployed engineers integrate 5 benchmarks, and started fixing what slows the framework down. By 6 months one part of it is yours, for example scaling the runs, observability, or a group of related benchmarks, and a release will have gone out on your numbers. By 12 months you'll know the design and trade-offs of the whole evaluation system, and be the person the rest of H asks about evaluations.

Who you'd work with Ceiran Chapman, our VP Engineering, is hiring for this role. You'd join the evaluation team. The people relying on your work day to day are H's researchers and forward deployed engineers.

## What we think it takes

Likely a good fit if you

- Have spent 5+ years in backend development, with production Python at the core, and use coding agents to go faster without letting quality drop.
- Have built test, QA or evaluation tooling that other teams depended on, and care whether a number is right.
- Have operated distributed systems on Kubernetes in a public cloud. AWS experience helps most.
- Have built and shipped systems end to end, including APIs (REST or GraphQL) and integrations with outside services.
- Know relational and non-relational databases, and message queues such as SQS, RabbitMQ or Kafka.
- Instrument what you build, with metrics, tracing and monitoring from the start.

Stronger still if you have

- Measured LLM quality before, or built agents yourself.
- Packaged and run workloads in Docker and on virtual machines.
- Used Temporal, Dask, FastAPI, PostgreSQL, Grafana or Datadog.
- Automated web or desktop software with Playwright, Selenium or a browser extension you wrote.
- Set standards other engineers follow, through code review, design review or mentoring.

You do not need a background in machine learning. We'll work that out with you. If you match most of this but not all of it, apply anyway.

## How we hire

A 30 minute call with our Talent team, a 60 minute technical challenge, a 60 minute system design interview, and a 30 minute final conversation with Ceiran. About 3.5 hours in total.

Practicalities Paris posting: Hybrid in Paris. That means 3 office days a week and a London trip about once every 4 to 6 weeks. There is a London posting for the same role. We offer a competitive package.

## About H Company

## Company Overview
- **One-liner**: H Company builds a full-stack enterprise platform for deploying autonomous AI agents that can navigate digital workflows, fill forms, and complete tasks across browsers and enterprise systems.
- **Entity Type**: Private (Venture Capital-Backed; Seed stage)
- **Headquarters**: Paris, France (with a hub in London, UK)
- **Founded**: 2023
- **Founders**: Gautier Cloix (CEO), Laurent Sifre (Chair of the Scientific Committee); leadership team includes Maxime Defauw, Caroline Charra, Pierre-Louis Cedoz, and Géraldine Lafontaine [hcompany.ai/team](https://hcompany.ai/team)

## Core Business
- **Primary industry**: Business/Productivity Software; Artificial Intelligence & Machine Learning; Automation/Workflow Software [pitchbook.com](https://pitchbook.com/profiles/company/597244-24)
- **Target customers**: Global enterprises (B2B)
- **Mission**: Build AI systems that powerfully and reliably work in the real world, enabling teams to focus on what matters by letting AI do the rest [hcompany.ai](https://hcompany.ai/)

## Products & Services
- **Holo Models API (Holo3)**: Multimodal AI models designed to interpret content and operate across real-world digital workflows. Available via API for enterprise integration.
- **HoloTab**: A Chrome extension that deploys an AI agent inside the browser. It navigates websites, fills out forms, and completes tasks on behalf of the user. Users can create "Routines" to automate manual chores.
- **Autonomous Enterprise Operations Platform**: A full-stack enterprise platform combining models, advanced agents, scalable execution, and continuous learning for deploying "action-oriented AI" in production.

## Market Standing
- **Valuation**: Not publicly disclosed (Privately held)
- **Total Funding**: $220M raised (Seed Round completed May 2024) [pitchbook.com](https://pitchbook.com/profiles/company/597244-24)
- **Key Metric**: 90 employees (as of 2026); generating revenue [pitchbook.com](https://pitchbook.com/profiles/company/597244-24)
- **Notable Investors/Partners**: Accel, Aglaé Ventures, Amazon.com, Auriga Cyber Ventures, La French Tech (24 total investors) [pitchbook.com](https://pitchbook.com/profiles/company/597244-24)
- **Growth Signals**: Acquired Mithril Security (Jan 2024); maintains a wholly-owned subsidiary H.Ai Technology in London; active hiring across Research Lab, Forward Deployed Engineering, and Product Development teams

## Competitive Advantages
- **Full-stack approach**: Combines proprietary multimodal models, browser-based agents (HoloTab), and enterprise orchestration into a single platform rather than point solutions.
- **Deep research foundation**: Leadership includes former foundational AI researchers who have scaled products used by governments and the world’s largest enterprises [hcompany.ai/team](https://hcompany.ai/team)
- **First-mover in browser-based enterprise agents**: HoloTab competes in the emerging "AI agent doing work in your browser" category, differentiated by enterprise-grade reliability and routine automation.
- **Strong investor syndicate**: Backed by Accel, Aglaé Ventures, and Amazon.com — signaling confidence in enterprise AI deployment.

## Strategic Focus
- Scaling agentic AI from browser extensions (HoloTab) to full enterprise-wide autonomous operations
- Expanding the Holo Models API (Holo3) as a platform for third-party developers and enterprise integrations
- Growing the Forward Deployed Engineering (FDE) team to customize solutions for large enterprise clients
- Continuing research into reliable, action-oriented AI systems that can be trusted in production environments

## Why Work Here
- **Culture**: Described as "fast-moving, creative, and collaborative" with a "high-trust, multicultural environment." Values include integrity, curiosity, impact-first mentality, and "ship fast, learn faster" [hcompany.ai/careers](https://hcompany.ai/careers)
- **Work style**: Hackathons spark bold ideas, regular offsites, team celebrations. "Everyone’s empowered to take initiative, fix what’s broken, and own outcomes." [hcompany.ai/careers](https://hcompany.ai/careers)
- **Team composition**: A blend of deep research expertise and hands-on experience building and deploying mission-critical technology at global scale. Teams include Research Lab, Forward Deployed Engineering, and Product Development [hcompany.ai/team](https://hcompany.ai/team)
- **Locations**: Headquarters in Paris, hub in London. Roles likely span both offices with flexibility (policy not explicitly stated).
- **Role types actively hiring**: Research, Forward Deployed Engineering, Product Development [jobs.ashbyhq.com/hcompany](https://jobs.ashbyhq.com/hcompany)

## Sources
1. [hcompany.ai](https://hcompany.ai/) — Official website with product descriptions, mission, and platform overview
2. [hcompany.ai/team](https://hcompany.ai/team) — Leadership team, values, and team structure
3. [hcompany.ai/careers](https://hcompany.ai/careers) — Culture, values, and hiring philosophy
4. [jobs.ashbyhq.com/hcompany](https://jobs.ashbyhq.com/hcompany) — Active job openings
5. [pitchbook.com](https://pitchbook.com/profiles/company/597244-24) — Funding history, valuation, investors, employee count, and acquisition data

## Other roles at H Company

- [Digital Manager](https://feeny.ai/job/digital-manager-h-company-paris-cym5dpsb2ned) — Paris, France
- [Content Manager](https://feeny.ai/job/content-manager-h-company-paris-ksf7evcjs497) — Paris, France
- [Social Media and Content Strategist - Community](https://feeny.ai/job/social-media-and-content-strategist-community-h-company-paris-aq4wcyhgk9dm) — Paris, France
- [Business Partner / Executive assistant to CEO](https://feeny.ai/job/business-partner-executive-assistant-to-ceo-h-company-paris-fvv7y2xhvbg6) — Paris, France
- [Infrastructure Engineer (ML Compute) - London](https://feeny.ai/job/infrastructure-engineer-ml-compute-london-h-company-london-4ns334xrmxmc) — London, United Kingdom
- [Infrastructure Engineer (ML Compute) - Paris](https://feeny.ai/job/infrastructure-engineer-ml-compute-paris-h-company-paris-mnpet23ae537) — Paris, France
- [Product Designer - Paris](https://feeny.ai/job/product-designer-paris-h-company-paris-x0q7jf2tsexe) — Paris, France
- [Product Designer - London](https://feeny.ai/job/product-designer-london-h-company-london-88e2tsm70qwt) — London, United Kingdom
- [Senior Full Stack Engineer](https://feeny.ai/job/senior-full-stack-engineer-h-company-london-hpack26mhfaa) — London, United Kingdom
- [Technical Lead, Observability - Paris](https://feeny.ai/job/technical-lead-observability-paris-h-company-paris-53k7x9425fje) — Paris, France