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AI role · Open offer
Offre d'emploi full remote France — Ingenieur IA
HexaFlow AI Operations
This listing is optimized for AI-native talent: clear skills and tools so candidates know if they fit before they apply—and so you spend less time screening mismatches.
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At a glance
How you'll work, where, and key listing dates.
- Employment
- Freelance, Full-time
- Workplace
- Remote
- Location
- France · Full remote
- Compensation
- EUR 65k-85k/year + prime performance
- Experience level
- Senior
- Team
- AI operations
- Benefits & perks
About this role
What the team is looking for and how this position fits.
HexaFlow AI Operations is hiring a Senior Offre d'emploi full remote France — Ingenieur IA on the AI operations team (Remote · Paris, France). This is a hands-on role in LLM & generative AI—not a generic “AI enthusiast” post.
You will own LLM features, retrieval, agents, and evaluation end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.
HexaFlow AI Operations recrute un profil capable de concevoir, automatiser et maintenir des workflows IA pour les equipes operations et support.
Full remote France avec 2 rencontres equipe par an.
HexaFlow AI Operations needs someone who can move LLM features, retrieval, agents, and evaluation from experiment to production—with tests, monitoring, and stakeholder-ready communication.
The AI operations group partners closely with product and domain experts; you will translate ambiguous requirements into measurable ML or LLM outcomes.
What you will do
- Design and ship LLM features, retrieval, agents, and evaluation with offline evals, dashboards, and rollback plans.
- Improve datasets, labeling, and metrics that correlate with user or business outcomes.
- Review model changes for safety, bias, latency, and infrastructure cost before wide release.
- Document decisions so on-call, support, and compliance teams can act without guesswork.
- Collaborate async with written specs, demos, and recorded design reviews.
What we look for
- Demonstrated production use of core skills such as Python, Automation, OpenAI API, SQL—with repos, writeups, or metrics we can verify.
- Comfort operating the listed toolchain (n8n, Notion) in real environments—not tutorials only.
- Ownership of at least one feature or model from design through post-launch review—including failure modes you handled.
- Clear communication on trade-offs (quality, cost, latency, safety) with product and non-technical stakeholders.
- Eligible to work in France (or remote policy as stated in the listing).
Benefits & ways of working
- Budget home office, mutuelle premium, coworking stipend.
Skills we're hiring for
What each capability means for this role—not a keyword checklist.
- Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
- Automation
Practical Automation experience applied to LLM features, retrieval, agents, and evaluation in production or rigorous pilots.
- OpenAI API
Tools & stack
Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).
- n8nTool
Regular use of n8n in the LLM & generative AI stack—configuration, debugging, and team conventions.
- NotionTool
Regular use of Notion in the LLM & generative AI stack—configuration, debugging, and team conventions.
You're a strong fit if…
Tailored to this listing—use it as a self-check before you apply.
- ✓You can show evidence in your application: Partagez un exemple concret de workflow automatise (n8n/Make/Zapier) avec resultat mesure.
- ✓Several of these show up in recent shipped work—not only on your CV: Python, Automation, OpenAI API, SQL, and n8n.
- ✓You have owned LLM features, retrieval, agents, and evaluation in production: debugging live issues, running postmortems, and iterating from real user or business signals.
- ✓You communicate clearly in writing, document decisions, and can overlap with the team’s core hours for pairing and incident response.
- ✓You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.
Apply
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What the employer asked for
Partagez un exemple concret de workflow automatise (n8n/Make/Zapier) avec resultat mesure.
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