As part of our business growth, we are looking for a Data & AI Architect passionate about new technologies, capable of designing, managing and industrializing high value-added Big Data and GenAI solutions for our clients.

Your tasks

Framing & Tech Architecture: Design target architectures (Batch, Real-Time, Cloud and On-Premise) and technically manage projects from POC to industrialization.

Data & AI Pipelines: Develop and orchestrate massive data processing (PySpark) and AI inference pipelines.

GenAI & RAG Architectures: Implementing and optimizing advanced RAG solutions interconnected with language models (LLM) and vector databases.

Streaming & Ingestion: Setting up high-performance real-time streams (Kafka, NiFi) connected to data and AI engines.

Industrialization & MLOps/DevOps: Implement CI/CD pipelines, flow orchestration, monitoring and ensure performance, security and data quality.

Leadership & Steering: Provide technical guidance to teams (Data, AI, Cloud), ensure project monitoring and explain architectural choices to Business and Product teams.

Technical skills required

Big Data & Processing: Proficiency in PySpark (Batch & Streaming) and distributed environments (Hadoop/Cloudera, HDFS).

Streaming & Ingestion: Solid expertise in Kafka and NiFi for real-time data processing.

Databases (NoSQL & Vector): Experience with Cassandra/Hive as well as vector databases (Pinecone, FAISS, Weaviate or ChromaDB).

GenAI & AI Frameworks: Mastery of LLMs (OpenAI/Azure OpenAI, Claude, Mistral...), Prompt Engineering and associated frameworks (LangChain, LlamaIndex).

DevOps, MLOps & Orchestration: Solid CI/CD practices (GitLab, Docker), Python/FastAPI scripts and orchestration tools (Airflow, Prefect).

Cloud & DBMS: Good understanding of Cloud architectures (Azure, AWS or GCP) and proficiency in SQL.

Desired Candidate Profile

Desired profile

Education: Bac+5 in computer science, software engineering, Data Science, AI or equivalent.

Experience: Proven experience in Data Architecture (~8 years and more) in Data Engineering and integration of AI solutions.

Skills: Technical leadership, analytical mind, communication skills and autonomy.

Languages: Technical English required.