GenAI Engineer

At Pluxee, we shape the world of employee benefits and engagement by bringing to life a personalized and sustainable employee experience, at work and beyond.

Tous les candidats potentiels sont encouragés à parcourir et à lire la description complète du poste avant de postuler.

Permanent Regular

Job Description:

Pluxee is a global leader in employee benefits and engagement, operating in 26 countries. As part of its digital transformation, Pluxee has built an internal AI platform giving employees access to LLMs with strong data sovereignty, compliance, and business integration guarantees.

As generative AI matures and cross-functional needs grow — AI agents, RAG, tool integrations, AI-assisted development practices (AIDLC) — Pluxee is creating the GenAI Engineer role to own this ambition in-house.

This is a hands-on technical role combining ownership of a production AI platform with a GenAI advisory function for IT teams across the group.

2. Key Responsibilities
A. Internal AI Platform Ownership

• 
  
• Own the technical roadmap: platform evolution, updates, and new integrations (MCP connectors, business tools…)
  
• Ensure reliability, security, and performance of the production platform (Kubernetes / Azure, CI/CD, monitoring).
  
• Design and deploy business AI agents: system prompts, tools, knowledge bases, per-team or per-BU access control.
  
• Manage the LLM integration layer: model routing, guardrails, token quotas, cost management.
  
• Drive the architecture toward a multi-tenant platform: agents and knowledge bases scoped per Business Unit.
  
• Operate existing and new MCP (Model Context Protocol) servers: Atlassian (Jira / Confluence), web search, and upcoming connectors (SharePoint, etc.).
  

B. GenAI Support for IT Practices — AIDLC

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• Define and roll out AIDLC (AI-assisted Development Lifecycle) standards: integrating AI into code review, generation, testing, and documentation workflows.
  
• Support development teams in adopting GenAI tools (code assistants, agents, RAG on codebases).
  
• Identify priority AI use cases across IT departments and co-build solutions with the teams.
  
• Act as the GenAI technical reference: architecture, model selection, security, GDPR and EU AI Act compliance.
  
• Lead technology watch on the GenAI ecosystem and bring forward concrete, actionable proposals.
  

Experience

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• 5+ years in backend / full-stack development, including at least 2 years on GenAI / LLM systems in a production context.
  
• Proven experience deploying and operating AI platforms on cloud infrastructure (Azure preferred; AWS or GCP accepted).
  
• Background in international or multi-BU enterprise environments is a plus.
  

Technical Skills

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• GenAI ecosystem:LLM & Agents —
  
• RAG (vector indexing,pgvector, Elasticsearch), prompt engineering, multi-agent chains
  
• Model Context Protocol (MCP) — design and operation of MCP servers
  
• LLM proxies (LiteLLMor equivalent), Azure OpenAI / AI Foundry,guardrailsand quota management
  
• Infrastructure:Cloud & DevOps —
  
• Kubernetes (AKS), Helm, Docker, CI/CD (Azure DevOps or GitHub Actions)
  
• Secrets management (Azure Key Vault or equivalent), monitoring (Datadog or equivalent)
  
• Stack:Development —
  
• Python (Flask, orchestration scripts), Node.js / TypeScript
  
• MongoDB, PostgreSQL, Redis,MeiliSearch
  
• Protocols:Security & Auth —
  
• OpenID Connect, OAuth 2.0 (3LO), Azure AD / Okta, JWT
  
• GDPR compliance, EU AI Act, data residency (EU hosting)
  

Soft Skills

• 
  
• Ability to translate complex technical topics for non-technical stakeholders.
  
• Results-oriented:knowshow to move from POC to production with rigor.
  
• Proactive on technologywatch:tracks the fast-moving LLM/agent ecosystem.
  
• Collaborative mindset in an international,distributed-teamcontext.
  

Languages

• 
  
• Professional English (documentation, international meetings) — French is a plus.
  

4. Technical Environment

The GenAI Engineer operates within the following environment (at time of joining):

AI Platform: Internal AI chat platform based onLibreChat, deployed on Azure AKS (EU)

LLM:Azure AI Foundry (GPT-5, GPT-4.1) viaLiteLLMProxy

MCP Connectors:Atlassian (Jira/Confluence), web search — upcoming: SharePoint,Rovo

Databases:MongoDB, PostgreSQL +pgvector, Redis,MeiliSearch

CI/CD & Quality:Azure DevOps Pipelines, SonarQube,Snyk, pre-commit

Auth:Okta SSO (OpenID Connect), A