AI Engineer

Jobtailor; Antwerpen; Sur place; EUR 80 000 - 120 000; Plein temps

Résumé du poste

Jobtailor is seeking an AI Engineer to bring AI models into the Yuki product and build capabilities that users interact with directly. You will land predictions and GenAI features for accountants and entrepreneurs, ship compound AI systems, and productionize models with APIs and latency focus.

You will collaborate with Product and Design to identify new use cases, shape the roadmap, and build MCP-based capabilities in a fast-paced environment.

Qualifications

• You have a strong AI software engineering background with proven production experience.
• You are proficient with Python, Databricks, vector databases, MLflow, and APIs.
• You understand GenAI patterns (RAG, agents) and orchestration.
• You can co-create with Product and Design to shape features and roadmaps.
• You have experience in building MCP-based capabilities is a plus.

Responsabilités

• You land AI predictions and GenAI features in front of users with robust performance.
• You build GenAI capabilities and in-product prompt orchestration.
• You productionize models with serving, APIs, and latency focus.
• You support in-product vector search and retrieval integration.
• You integrate AI predictions into the .NET backend with the team.
• You collaborate with Product and Design to identify new use cases and roadmap items.

Connaissances

AI in production

Python

GenAI patterns

API design

English fluency

C#/.NET (nice to have)

MLOps tooling

Vector databases

MLflow

Outils

Databricks

Description du poste

As our AI Engineer, your mission is to take AI models into the Yuki product and build the capabilities users actually touch.

Responsibilities

• You get predictions and GenAI features to land robustly, performantly, and reliably in front of our accountants and entrepreneurs.
• Build GenAI capabilities: Ship compound AI systems, retrieval-augmented features, and in-product prompt orchestration.
• Productionize models: Own serving, APIs, runtime performance, and latency so AI lands reliably in the live app.
• Serve retrieval: Build in-product vector search and retrieval integration, and be first response for model-quality regressions in production.
• Land it in the product: Integrate AI predictions into the .NET backend alongside our backend engineers.
• Co-create with Product: Spot new use cases, help shape the roadmap, and build features (including MCP-based capabilities) with Product and Design.

Qualifications

• Strong AI software engineering background (min 3 years), with real experience putting ML/AI into production at scale.
• Hands‑on with the stack: Python, Databricks, vector databases, MLflow (serving and monitoring side), and solid API design.
• Comfortable with GenAI application patterns: RAG, agents, and orchestration (experience with an AI agent framework is a big plus).
• A product‑minded builder: you think about use cases, not just tickets, and can co‑create with Product and Design.
• Nice to have: C# (.NET), MLOps tooling, and experience building MCP for a tool or platform.
• Fluent English is a must.