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TRCI-26-05106
AI Platform Architect (LLMOps / MLOps, RAG)
Contract AI Platform Architect to design, scale, and secure an AI platform delivering real-time AI services to thousands of users. The role bridges ML engineering and DevOps/SRE, focusing on industrializing the platform (LLMOps/MLOps), implementing fit-for-purpose RAG architectures (advanced/graph/agentic), optimizing cloud/Kubernetes infrastructure and GPU/CPU utilization, and ensuring privacy-by-design, governance, and compliance (GDPR/AI Act) including sovereignty requirements. Key deliverables include vector database design, model/prompt lifecycle management, cost-optimized inference, response quality evaluation (hallucination mitigation), re-ranking, and source traceability/citations.
Position summary
- Location
- France
- Workplace
- On-site
- Employment
- Contract
- Experience
- Minimum 5 years and Maximum 15 years
Role overview
Why This Role Matters.
Contract AI Platform Architect to design, scale, and secure an AI platform delivering real-time AI services to thousands of users. The role bridges ML engineering and DevOps/SRE, focusing on industrializing the platform (LLMOps/MLOps), implementing fit-for-purpose RAG architectures (advanced/graph/agentic), optimizing cloud/Kubernetes infrastructure and GPU/CPU utilization, and ensuring privacy-by-design, governance, and compliance (GDPR/AI Act) including sovereignty requirements. Key deliverables include vector database design, model/prompt lifecycle management, cost-optimized inference, response quality evaluation (hallucination mitigation), re-ranking, and source traceability/citations.
Your Impact
Deliver Enterprise Value
Help organisations solve complex business problems through modern technology, consulting expertise and measurable outcomes.
Collaboration
Work Across Teams
Collaborate with consultants, architects, engineers and client stakeholders throughout the project lifecycle.
Growth
Learn Continuously
Gain exposure to enterprise technologies, certifications, mentoring and real-world project experience.
Career Path
Grow With Ubique
Build a long-term consulting career with opportunities to take on greater responsibility and leadership over time.
Responsibilities
What You'll Be Doing.
Every role at Ubique contributes directly to solving meaningful business challenges for our clients.
02
Your mission is to design and build the technological "backbone" that powers our AI platform. You need to transform rich, massive document holdings into seamless, secure, and high-performance AI services.
03
Industrialization of the AI Platform: Improve and scale the platform and the underlying infrastructure of AI services capable of serving thousands of users in real time.
04
Implementation of the right RAG (Retrieval-Augmented Generation) architecture: Depending on the use cases, know how to orchestrate RAG architectures (Advanced vs Graph vs Agentic), Design the architecture to inject expert data into the models to guarantee the excellence of the responses.
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Privacy "By Design": Ensuring that customer queries (often subject to professional secrecy) are handled with the highest level of security.
06
Industrialization (MLOps): Set up automated pipelines for model deployment and monitoring. Ability to challenge FINMLOPS and optimize the cost of the platform.
07
Scalability and Performance: Ensuring that the platform supports scalability and optimizes resource utilization (GPU/CPU).
08
Governance and Security: Ensure data protection and compliance with ethical and regulatory standards (GDPR, AI Act).
09
Sovereignty: Participate in the implementation of a platform that complies with our customers' sovereignty requirements.
10
Design and optimize the Vector Database containing the group's information assets.
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Manage the prompt lifecycle and eventual fine-tuning of specialized models for legal. Infrastructure & Scalability
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Manage the Cloud infrastructure of the AI platform and Kubernetes orchestration.
Technology stack
Tools & Technologies.
The platforms and technologies you'll use to build modern, enterprise-grade solutions.
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LLMOps
Required
02
MLOps
Required
03
RAG
Required
04
Retrieval-Augmented Generation
Required
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Vector database
Required
06
Re-ranking
Required
07
Hallucination mitigation
Required
08
Prompt lifecycle
Required
09
Fine-tuning
Required
10
Kubernetes
Required
11
Cloud infrastructure
Required
12
GPU
Required
13
CPU
Required
14
Token management
Required
15
Monitoring
Required
16
GDPR
Required
17
EU AI Act
Required
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Data sovereignty
Required
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Model orchestration
Required
Requirements
Skills & Experience.
We value curiosity, collaboration and continuous learning. If you don't meet every requirement but believe you can make an impact, we'd still love to hear from you.
Essential
Required Qualifications
AI platform architecture for LLM-based services
RAG architecture design and orchestration (advanced/graph/agentic)
MLOps/LLMOps: automated deployment and monitoring pipelines
Kubernetes orchestration
Cloud infrastructure management for AI platforms
Vector database design and optimization
Security and privacy-by-design for sensitive queries
Scalability and performance optimization (GPU/CPU resource utilization)
Governance/compliance awareness (GDPR, AI Act)
Inference cost optimization (token management)
Quality evaluation for LLM outputs (relevance measurement, hallucination mitigation)
Re-ranking architecture implementation
Traceability of sources / citations in AI responses
Preferred
Nice to Have
Fine-tuning specialized models (legal domain mentioned)
SRE/DevOps practices for high-availability real-time services
Experience with sovereignty constraints (data residency, sovereign cloud patterns)
Experience challenging/optimizing FinMLOps cost models
What you'll gain
More Than Just A Job.
We're committed to helping every team member grow professionally, personally and technically while working on meaningful projects.
Global Exposure
Collaborate with international clients and multicultural teams on enterprise programmes.
Continuous Learning
Expand your expertise through mentoring, certifications and hands-on project experience.
Career Growth
Take ownership, develop leadership skills and grow your consulting career over time.
Flexible Working
Hybrid and remote collaboration designed around trust and delivering exceptional outcomes.
People First
Join a supportive culture where collaboration, respect and long-term relationships come first.
Enterprise Projects
Work on meaningful technology initiatives for leading organisations across industries.
Apply
Apply for AI Platform Architect (LLMOps / MLOps, RAG)
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