AI & DATA ENGINEER

AI & Data Engineer

Purpose of the Role

The AI & Data Engineer designs, builds, and operationalises advanced data and AI solutions within a regulated environment. The role supports transformation initiatives by enabling scalable analytics, machine learning, and LLM-based systems, ensuring robustness, performance, and compliance throughout the AI lifecycle.

Key Responsibilities

Data Engineering & AI Development

• Design and maintain data pipelines and data products for analytics and AI use cases.
  

• Develop hybrid data architectures (on-premise / cloud).
  

• Implement CI/CD automation, testing frameworks, and industrialised delivery processes.
  

Machine Learning & Advanced Analytics

• Develop, deploy, and monitor machine learning models (e.g., fraud detection, AML/KYC, performance analytics).
  

• Conduct experimentation and prototype evaluation using structured metrics.
  

• Translate research into production-ready solutions and support code reviews.
  

AI & LLM Engineering

• Build solutions for OCR, document classification, information extraction, and retrieval-augmented generation (RAG).
  

• Design prompt templates, evaluation datasets, and LLM interaction workflows.
  

• Integrate modern AI platforms and tools into operational processes.
  

Architecture & MLOps

• Integrate AI models into business systems via APIs, microservices, and orchestration layers.
  

• Ensure secure, production-grade deployments with monitoring, versioning, and governance.
  

Stakeholder Collaboration

• Produce technical documentation and communicate insights to both technical and business stakeholders.
  

• Support risk, compliance, and business teams to ensure responsible AI adoption.
  

Skills & Experience

Required

• 5+ years of experience in data engineering, data science, or AI roles within regulated environments.
  

• Strong expertise in Python, SQL, Git, and modern data/AI tooling.
  

• Experience designing large-scale data pipelines.
  

• Solid knowledge of machine learning, NLP, vector search, and model evaluation.
  

• Experience with platforms such as Dataiku, Snowflake, or other big data environments.
  

• Fluency in French and English.
  

Preferred

• Experience with LLM frameworks, prompt engineering, and document-intelligence workflows.
  

• Knowledge of OCR technologies (e.g., Tesseract, OpenCV).
  

• Exposure to MLOps/DevOps practices (CI/CD, APIs, containers).
  

• Understanding of banking processes, AML/KYC, risk, and regulatory frameworks.
  

Qualifications

• Master’s degree or higher in Computer Science, Data Science, Mathematics, or related fields.
  

• 5+ years of professional experience in data engineering, data science, or AI within regulated industries.
  

• Relevant certifications (Dataiku, Snowflake, Python) are a plus.
  

• Languages: Fluent French and English.