arizeai
Forward Deployed AI Engineer, EMEA
At a Glance
- Location
- EMEA
- Compensation
- tion for this role is between $125,000 - $175,000, plus a competitive equity pac
- Posted
- 2026-03-28T01:00:26-04:00
Key Requirements
Required Skills
Domain Knowledge
- Engineering
- Medical
Requirements
Comfortable working in public Cloud environments (AWS, Azure, GCP)
Knowledge of machine learning frameworks such as TensorFlow, PyTorch or Scikit-learn
Knowledge of LLM / Agentic frameworks such as Llamaindex, LangGraph, and DSPy
Understanding of ML/DS concepts, model evaluation strategies and lifecycle (feature generation, model training, model deployment, batch and real time scoring via REST APIs) and engineering considerations
Understanding of GenAI concepts and application evaluation + development lifecycle
Proficiency in a programming language (Python, JS/TS, Java, Go, etc)
Responsibilities
Work closely with some of the most sophisticated ML / GenAI teams in the world.
You will act as a trusted advisor to our customers, while also building relationships with technical and business stakeholders.
Advise on GenAI and ML best practices
Give ML and LLM product demos to technical and business stakeholders
Run strategic business reviews for customers in partnership with our sales team
Interface with our pre-sales engineering team to gather client goals and KPI’s.
Team
Our engineering team builds systems that interact with some of the most complex software ever deployed in production. The team is composed of industry veterans that have built deep learning infrastructure, autonomous drones, ridesharing marketplaces, ad tech and much more.
We are looking for a client-obsessed AI Solutions Engineer with entrepreneurial tendencies to join the good fight and help build out our Solutions Engineering org. You’ll be the trusted technical advisors for our customers, driving business value, offering advice, and growing accounts. You’ll accomplish this by leading customers to solutions oftentimes by teaching the product to new users or consulting on best practices. You must be ready for technical discussions with data scientists and engineers, then demonstrate the value of Arize in business discussions with directors and executives. The goal is to enable our customers to become successful and enthusiastic about Arize.