1 day ago

Remote AI Engineer - Agents (m/f/d)

RoomPriceGenie

Netherlands

1 day ago

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RoomPriceGenie is seeking an AI Engineer (Agents) to build and operate production AI agents for hotel pricing optimization. The role involves designing, deploying, and maintaining agentic systems with LLMOps, evaluation, and safety. Requires strong engineering fundamentals, Python/TypeScript, and experience with LLM applications. Fully remote within Europe.

AIRemoteFull-timeEntry LevelPythonTypeScript

Remote AI Engineer - Agents (m/f/d)

Apply

AIRemoteFull-timeEntry LevelPython

Salary

Not specified

Work Location

Netherlands, NL

Work Model

Fully remote within Europe

Employment Type

Full-time

Experience Level

Not Applicable

Core Qualifications

Technical (Must-have)

PythonTypeScriptAPIsAWSDatabricksSnowflakeLLMOpsAI agentstool-callingworkflow orchestrationcontainerizationevaluationobservabilitytracingasynchronous workflows

Soft Skills

product-mindedevidence-drivencollaborationownershipcommunication

Preferred Qualifications

Technical (Nice-to-have)

Dagsterdbtmodern AI frameworks

Key Responsibilities

•Design, build, deploy, and operate production AI agents and supervised workflows.
•Integrate models and agent workflows with APIs, databases, internal systems, and approved tools.
•Create evaluation harnesses and test datasets to measure task success, accuracy, groundedness, safety, latency, cost, and exception rate.
•Implement LLMOps foundations: tracing, prompt and configuration versioning, monitoring, alerting, model routing, cost caps, and rollback/kill-switch mechanisms.
•Define autonomy gates, human-in-the-loop review, escalation paths, and operational runbooks.
•Improve agents through production feedback, failure analysis, and disciplined iteration.
•Build reusable agent components and patterns.
•Stay hands-on in code, system design, debugging, and technical decision-making.

AI EngineerAgentsLLMLLMOpsPythonTypeScriptAWSDatabricksSnowflakeRemote

Key Responsibilities

•Design, build, deploy, and operate production AI agents and supervised workflows.

•Integrate models and agent workflows with APIs, databases, internal systems, and approved tools.

•Create evaluation harnesses and test datasets to measure task success, accuracy, groundedness, safety, latency, cost, and exception rate.

•Implement LLMOps foundations: tracing, prompt and configuration versioning, monitoring, alerting, model routing, cost caps, and rollback/kill-switch mechanisms.

•Define autonomy gates, human-in-the-loop review, escalation paths, and operational runbooks.

•Improve agents through production feedback, failure analysis, and disciplined iteration.

•Build reusable agent components and patterns.

•Stay hands-on in code, system design, debugging, and technical decision-making.