مهندس بيانات وذكاء اصطناعي
تفاصيل الوظيفة
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 responsibilities:
- 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.
Required technical skills:
Big Data & Processing: Mastery of 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 on Cassandra/Hive as well as on vector databases (Pinecone, FAISS, Weaviate or ChromaDB).
GenAI & Frameworks IA : Ma trise des LLM (OpenAI/Azure OpenAI, Claude, Mistral...), du Prompt Engineering et des frameworks associants (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 mastery of the SQL language.
Desired Candidate Profile
Search 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.
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