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AI Engineer (Enablement)(m/w/x)
Building and maintaining production-grade AI systems with LLMs and agents for a European mobility app. Experience with LLM failure modes and evaluation frameworks required. Flexible working arrangements, LinkedIn Learning access.
Requirements
- Strong experience as AI Engineer, ML Engineer, or Senior Software Engineer with modern AI systems
- Built or operated LLM-based systems in production
- Understanding of LLM failure modes (hallucinations, non-determinism, evaluation challenges)
- Balancing speed, quality, and pragmatism in production AI systems
- Designing evaluation frameworks and defining quality metrics for AI behavior
- Solid backend engineering fundamentals (APIs, services, data access)
- Enjoyment of working across teams and explaining complex AI concepts clearly
- Caring about reliability, safety, and real business impact
- Fluent in English
- Experience with agentic systems or multi-step workflows
- Familiarity with AI governance, risk, or compliance considerations
- Experience enabling other teams through platforms, SDKs, or internal tools
- Prior work in marketplaces, mobility, or large-scale consumer products
Tasks
- Design and build production-grade AI systems
- Maintain AI systems using LLMs, agents, and retrieval-based architectures
- Develop and evolve the AI Evaluation Framework
- Conduct multi-turn evaluations
- Measure quality, safety, and hallucination metrics
- Evaluate AI systems using offline and production data
- Ensure AI solutions are compliant, observable, and trustworthy
- Collaborate with Product, Engineering, Legal, and Security teams
- Support and scale internal AI products
- Enable teams with shared tooling, patterns, and best practices
- Build reusable AI components
- Create RAG pipelines, agent orchestration, and model access layers
- Define standards for agent-ready architecture
- Integrate MCP and model abstraction
- Manage permissions for AI systems
- Monitor AI system performance, cost, and reliability
- Serve as a technical reference for AI across squads
- Support AI experimentation and rollout
Work Experience
- approx. 4 - 6 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Fluent
Benefits
Flexible Working
- Flexible working arrangements
Learning & Development
- LinkedIn Learning
Workation & Sabbatical
- Sabbatical and special leave policies
Corporate Discounts
- WeRoad partnership
More Vacation Days
- Birthday off
- 24th December off
- 31st December off
Other Benefits
- Short-term EU work policy
- Mobility Credit
Healthcare & Fitness
- Health insurance
Mental Health Support
- Employee assistance program
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AI Engineer (Enablement)(m/w/x)
Building and maintaining production-grade AI systems with LLMs and agents for a European mobility app. Experience with LLM failure modes and evaluation frameworks required. Flexible working arrangements, LinkedIn Learning access.
Requirements
- Strong experience as AI Engineer, ML Engineer, or Senior Software Engineer with modern AI systems
- Built or operated LLM-based systems in production
- Understanding of LLM failure modes (hallucinations, non-determinism, evaluation challenges)
- Balancing speed, quality, and pragmatism in production AI systems
- Designing evaluation frameworks and defining quality metrics for AI behavior
- Solid backend engineering fundamentals (APIs, services, data access)
- Enjoyment of working across teams and explaining complex AI concepts clearly
- Caring about reliability, safety, and real business impact
- Fluent in English
- Experience with agentic systems or multi-step workflows
- Familiarity with AI governance, risk, or compliance considerations
- Experience enabling other teams through platforms, SDKs, or internal tools
- Prior work in marketplaces, mobility, or large-scale consumer products
Tasks
- Design and build production-grade AI systems
- Maintain AI systems using LLMs, agents, and retrieval-based architectures
- Develop and evolve the AI Evaluation Framework
- Conduct multi-turn evaluations
- Measure quality, safety, and hallucination metrics
- Evaluate AI systems using offline and production data
- Ensure AI solutions are compliant, observable, and trustworthy
- Collaborate with Product, Engineering, Legal, and Security teams
- Support and scale internal AI products
- Enable teams with shared tooling, patterns, and best practices
- Build reusable AI components
- Create RAG pipelines, agent orchestration, and model access layers
- Define standards for agent-ready architecture
- Integrate MCP and model abstraction
- Manage permissions for AI systems
- Monitor AI system performance, cost, and reliability
- Serve as a technical reference for AI across squads
- Support AI experimentation and rollout
Work Experience
- approx. 4 - 6 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Fluent
Benefits
Flexible Working
- Flexible working arrangements
Learning & Development
- LinkedIn Learning
Workation & Sabbatical
- Sabbatical and special leave policies
Corporate Discounts
- WeRoad partnership
More Vacation Days
- Birthday off
- 24th December off
- 31st December off
Other Benefits
- Short-term EU work policy
- Mobility Credit
Healthcare & Fitness
- Health insurance
Mental Health Support
- Employee assistance program
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
FREENOW
Industry
Transportation
Description
The company empowers smarter mobility decisions, helping people to move freely and cities to thrive.
Not a perfect match?
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