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Automatically translated from French. View the original offer
FANELiT Digital Solutions is recruiting a Full-Stack Developer specializing in Data and Artificial Intelligence. The position covers the entire data value chain, from engineering and modeling to designing, training and orchestrating AI agents and systems. It is aimed at a versatile profile, comfortable as much on the development of APIs and backend services as on the problems of Data Science, MLOps and AI-driven development, in a logic "AI-driven" and "data-driven".
Main duties
1. Software development and engineering
Design, develop and maintain applications and services in Python, as well as other stack-based languages. Develop robust, secure and documented APIs (REST, GraphQL) to expose data and AI services. Participate in the technical architecture of solutions, particularly around microservices, orchestration and scalability. Apply good development practices: automated testing, code review, CI/CD and versioning.
2. Data Engineering and Data Science
Design and maintain data pipelines (ETL/ELT) for ingestion, transformation and provision of data. Model, clean and structure datasets for analytical and machine learning needs. Perform data analysis (Data Science / Data Analyst) to meet business needs and produce indicators. Build and industrialize machine learning and deep learning models in production environments.
3. Artificial Intelligence and Agent Orchestration
Design, develop and deploy AI agents, whether autonomous or multi-agent, to automate complex tasks. Implement AI orchestration architectures: agent frameworks, model chaining, RAG and function calling. Integrate language models (LLM) and generative AI services into business products and workflows. Ensure monitoring, evaluation and continuous improvement of deployed AI systems.
4. Software development driven by AI and data
Adopt and promote AI-enabled development practices, including code generation tools, AI co-pilots, and test automation. Design applications whose functionality and decisions are based on continuous data analysis. Contribute to the definition of internal standards for the integration of AI in the software development cycle.
5. Cloud and infrastructure
Deploy and operate solutions in cloud environments (AWS, Azure or GCP). Participate in the implementation of scalable infrastructure for hosting data pipelines and AI models, via containerization and orchestration. Contribute to the optimization of costs and performance of cloud and data architectures.
Technical skills required
Advanced mastery of Python and its ecosystem (Pandas, NumPy, FastAPI/Flask/Django, Pytest). Experience in API design and development (REST/GraphQL) and service architecture. Good knowledge of Data Engineering tools (Airflow, dBT, Spark, Kafka or equivalent). Experience in Data Science and Machine Learning (scikit-learn, PyTorch, TensorFlow). Knowledge of AI and LLM agent orchestration frameworks (LangChain, LangGraph, LlamaIndex or equivalent), RAG architectures and function calling. Mastery of relational and NoSQL databases (PostgreSQL, MongoDB, Redis, Snowflake/BigQuery data warehouses). Cloud experience (AWS, Azure or GCP) and DevOps/MLOps tools (Docker, Kubernetes, CI/CD, Terraform). Good culture of versioning and collaborative practices (Git, code review, technical documentation).
Cross-functional skills
Ability to work independently on complex and evolving technical topics. Technological curiosity and active monitoring of advances in AI and software engineering. The spirit of analysis and synthesis, methodological rigour. Good relationship and ability to collaborate with multidisciplinary teams (product, data, business). Sense of pedagogy to popularize technical subjects with non-experts.
Candidate profile
Bac Training+5 (engineering school, university) in computer science, data science or equivalent. Significant experience in software development, ideally in a Data/AI context. Concrete experience on generative AI or autonomous agent projects is a highly valued one. Technical English read and written essential for monitoring and documentation.
Benefits
Remuneration according to profile and experience. Flexible working arrangements, with in addition to salary bonuses depending on the projects. Stimulating environment, innovative projects with high technological content in AI and Data. International projects. Post Full-Stack + Data / AI. Structured and collaborative remote team. Continuous training and rapid skills development.
Education / Qualifications
Minimum level of study: Master.
Required documents
Curriculum vitae (CV).
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