Hybrid AI Engineer: Build Production-Grade AI at Scale

Mercedes-Benz.io GmbH; Lisboa; Hybride; EUR 70 000 - 90 000; Plein temps

Avantages offerts par ce poste

Health insurance

Life insurance

Flexible hybrid work model

Brand Connection perks

Résumé du poste

Mercedes-Benz.io is hiring an AI Engineer in Lisbon, Portugal, to shape the next generation of AI-powered products. You will design, build, and operate production-ready AI systems, working with Python, Kotlin, and TypeScript, collaborating with product teams and domain experts.

You will develop AI-powered applications, create retrieval and knowledge systems, and implement Responsible AI practices while ensuring reliability and observability in production environments.

Qualifications

• Proven software engineering background with production-ready systems.
• Hands-on experience building AI-powered apps with LLMs, prompts, and tool integrations.
• Strong understanding of AI system design, agent architectures and orchestration.
• Ability to evaluate technical and business trade-offs to pick appropriate solutions.
• Experience designing retrieval and knowledge systems including embeddings and RAG.

Responsabilités

• Analyze and decompose complex problems to identify AI value points.
• Evaluate models, frameworks, and technologies for production readiness.
• Design, build, and operate AI systems and agentic solutions at scale.
• Develop AI-powered applications using LLMs, prompts, outputs, and tool calls.
• Build retrieval and knowledge pipelines with embeddings and grounding.

Connaissances

Software engineering

LLM experience

AI system design

Retrieval systems

Tool integration

Trade-offs evaluation

Description du poste

Mercedes-Benz.io is hiring an AI Engineer in Lisbon, Portugal, to shape the next generation of AI-powered products. You will design, build, and operate production-ready AI systems, working with Python, Kotlin, and TypeScript, collaborating with product teams and domain experts.

You will develop AI-powered applications, create retrieval and knowledge systems, and implement Responsible AI practices while ensuring reliability and observability in production environments.