AI Operation Specialist

# Job Offer — AI Operation Specialist @ GENIAL

## Company Description

**GENIAL** (Generative IA Lab) is a Bordeaux-based company driving innovation in generative artificial intelligence. We design, build, and deploy cutting-edge AI solutions for clients in diverse industries — tourism, software publishing, nutraceuticals, retail, public investment, and more.

Our team builds conversational agents, callbots, and custom AI-powered applications that connect directly to our clients' business tools and data. We don't do AI for the sake of AI — we deliver measurable ROI and real adoption.

**Our mission**: Empower organizations with generative AI to transform operations, boost user experiences, and deliver tangible results through our **3U methodology** — Useful, Usable, Used.

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## Role Description

We are seeking an **AI Operation Specialist** to join our team full-time / part-time / freelance in **Bordeaux, France**.

This is a **hybrid role**: part hands-on AI builder, part project manager. You will start by taking ownership of existing AI agents deployed across multiple clients — understanding their feedback, learning the business logic, and driving continuous improvement. As you ramp up, you'll progressively take on new builds and contribute to use case scoping.

### What you'll do

**🔄 Continuous improvement of deployed agents (35%)**

- Take ownership of AI agents already in production for our clients

- Analyze client feedback, usage data, and conversation logs to identify improvement opportunities

- Deeply understand each client's business logic, domain, and workflows to make agents more relevant and reliable

- Implement prompt improvements, connector updates, behavior adjustments, and feature enhancements

- Monitor agent performance via observability tools (LangSmith, tracing, feedback loops, LLM-as-a-Judge)

- Drive a structured improvement cycle: measure → analyze → implement → validate → iterate

**📋 Project management & client delivery (30%)**

- Be the day-to-day contact for your clients throughout the project lifecycle

- Coordinate between internal teams (engineering, product, data science) and client stakeholders

- Run sprint reviews, demos, and feedback sessions with clients

- Track progress, anticipate risks, and ensure on-time delivery

- Manage multiple client projects simultaneously across different industries

**🤖 New agent design, build & orchestration (20%)**

- Design, build, and deploy new AI agents as you gain mastery of the stack: conversational agents, callbots, and custom AI-powered applications

- Architect RAG (Retrieval-Augmented Generation) pipelines with vector search on business document bases

- Orchestrate multi-agent systems

- Select and integrate the right tools & connectors for each client context (CRM, ERP, APIs, data sources)

**🎯 Use case scoping & discovery (15%)**

- Participate in discovery workshops alongside the commercial team

- Contribute to use case identification and feasibility assessment

- Translate business needs into functional specifications and technical architecture

### How the role evolves

```

Months 1-3  → Continuous improvement of existing agents, client feedback loops, learning the stack & business logic

Months 3-6  → Start building new agents from scratch, lead project delivery autonomously

Months 6+   → Contribute to scoping, architecture decisions, pre-sales support

```

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## Qualifications

### Must-have

- **Proven experience building and deploying AI agents** (conversational or task-oriented) in production environments using LLMs

- Strong proficiency with **LLM provider APIs** (OpenAI, Anthropic, Mistral) and orchestration frameworks (**LangChain, n8n, MCP**)

- Hands-on experience with **RAG architectures**, vector databases, and API integrations

- Solid development skills: **Python** and/or **TypeScript/Next.js/React**

- **Strong debugging and analytical skills** — you can read conversation logs, trace agent behavior, and diagnose prompt or pipeline issues quickly

- Ability to **understand business logic and domain context** to make agents smarter, not just technically functional

- Ability to **communicate clearly** with non-technical clients — present progress, manage expectations, explain trade-offs

- Excellent skills in **French and English**

- Daily usage of AI tools — AI-first problem solver

### Nice-to-have

- Experience with LLMOps: tracing, evaluation pipelines, LLM-as-a-Judge, LangSmith

- Experience managing project delivery in a tech/SaaS/consulting environment

- Experience with callbot/voice AI technologies (LiveKit, ElevenLabs, Deepgram)

- Cloud deployment experience (AWS, Docker, Vercel)

- Background in SaaS product delivery

- Knowledge of change management methodologies

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## What success looks like

| Timeframe | Milestone |

|-----------|-----------|

| **Month 1** | Onboarded on the Genial stack. Owning the continuous improvement cycle on 2-3 client agents — processing feedback, analyzing logs, shipping first improvements |

| **Month 3** | Deep understanding of your clients' business logic. Autonomous on the improvement cycle and client delivery. Starting to build new agent features from scratch |

| **Month 6** | Building and deploying new agents end-to-end. Trusted technical lead on your projects. Contributing to scoping and architecture decisions |

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## Why Join Genial?

🔥 **Real impact, not just POCs** — Every agent you build goes to production and serves real users

🛠️ **Builder first** — You ship agents, not slide decks. Hands-on, every day

🤝 **Client-facing autonomy** — You own your projects from build to post-deployment

📊 **Observability-first culture** — We trace, evaluate, and improve every agent continuously

🎯 **3U methodology** — We don't ship features, we ship adoption: Useful, Usable, Used

🧗‍♂️ **Bordeaux lifestyle** — Work from our Bordeaux office, enjoy the southwest

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📍 **Location**: Bordeaux, France

💼 **Contract**: Full-time / Part-time / Freelance

🏢 **Company**: GENIAL — Generative IA Lab (SAS CIBLER)

🌐 **Website**: wearegenial.com