Your Mission: You will play a key role in driving the success of “AI & Data-Driven” initiatives for our clients. Within a project, you will be responsible for both implementing agentic solutions and establishing data architecture and data processing workflows. You will be expected to:

• Contribute to client projects delivery from scoping and iterative development through to deployment and operational support.

• Understand client business challenges and needs, translating them into technical & data requirements.

• Assess the data ecosystem of the application to be developed or enhanced, proposing optimal approaches (architecture, tech stack, data sources, off-the-shelf vs custom model, etc.), presenting options and their impacts to stakeholders to guide decision-making.

• Collaborate with software engineers to define architecture and interfaces to embed AI & Data solutions into applications, APIs, or services.

• Sketch prototypes, and turn them into production-grade systems, ensuring data pipelines & AI systems are robust, scalable, monitored, and implement security best practices.

• Identify all required tasks and prerequisites, organize and sequence your work, estimate workloads, and highlight the critical path.

• Propose alternative approaches as needed to overcome challenges and ensure on-time, high-quality delivery.

Your Environment: 

• In client projects, you may work within a large cross-functional agile team (Architects, Data Scientists, DevOps Engineers, UX/UI Designers, Product Owners, Scrum Masters, Backend and Frontend Developers) or independently (with DevOps support mainly for deployment).

• Internally, you will contribute to Fieldbox shared expertise in “Data & AI-Driven” solutions: staying abreast of technological and scientific advancements, leveraging the open-source ecosystem, and mastering major cloud & SaaS platforms.

Personal Qualities:

• Business-value oriented

• Comfortable collaborating with multidisciplinary teams

• Ability to communicate complex topics effectively to diverse audiences

• Skilled in solving complex problems using varied approaches

• Fluent in English

Preferred Experience: 5+ years in Data & AI engineering, with a proven track record of deploying Data workflows & AI systems in production.

Mandatory:

• Ability to drive data solution architecture

• Proficiency in Python, with production-grade coding standards (tests, modularity, reproducibility….)

• Hands-on experience developing and industrializing agentic solutions (bonus for tools, human-in-the-loop, and advanced workflows)

• Experience with API design and development

• Experience working with diverse data and storage types (tabular, images, time series, SQL, object storage, etc.)

• Familiarity with at least one major data or cloud platform (GCP, AWS, Azure, Databricks, Snowflake, etc.)

Nice-to-Have:

• Knowledge of edge AI, on-premise deployment, or hybrid cloud environments.

• Experience with workload orchestration frameworks (e.g. Airflow, Argo, Metaflow)

• Experience with agentic cloud platform (e.g., Azure Foundry Agent Service, Vertex AI Agent builder, Amazon Bedrocks Agent)

• Ability to containerize applications (Docker) and setup CI/CD pipelines autonomously

Typical process includes 4 steps :

• HR interview,

• Technical Test,

• A technical interview with a Tech Lead,

• Interview with the management team to validate the application,

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