Senior AI Engineer

Deine Rolle im Team

Unsere Erwartungen an dich

Ausbildung

• Degree in Computer Science, Data Science, Machine Learning, Mathematics, Statistics, Physics, Engineering, or a related field - or equivalent practical experience.

Qualifikationen

• A strong track record of shipped systems counts as much as a formal qualification.
• Proven ability to take solutions from exploration to production - not just prototypes and notebooks.
• Demonstrated ability to manage and deliver complex projects with multiple stakeholders.
• Strong programming skills in Python; additional strength in TypeScript/Node.js, C#, Java, or Go is a plus, especially for building services and user-facing applications.
• Familiarity with ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn) and classical ML/NLP fundamentals.
• Exposure to MLOps/LLMOps practices: versioning, deployment pipelines, tracing, evaluation, and monitoring of AI systems in production.
• Version control and collaborative engineering practices (GitHub/GitLab).
• Nice to have: big data and analytics platforms (Snowflake, Spark, Databricks), data visualization, enterprise platforms (Microsoft 365 / SharePoint, SAP, Salesforce), or a research background with publications.
• Strong verbal and written communication:
• Ability to present ideas concisely and directly in international business contexts.
• Comfort proactively raising concerns, suggesting alternatives, and engaging in constructive debate.
• Curiosity about the business domain, not just the technology - the best AI solutions come from engineers who understand the problem deeply.
• Independent working style with a proactive approach to problem-solving.
• High level of ownership and accountability for project outcomes.
• Excellent teamwork and collaboration abilities.
• Effective project management and organizational skills.
• Fluent English required. German or Portuguese is beneficial but not mandatory.

Erfahrung

• 5+ years in software engineering, machine learning engineering, or data science roles, including meaningful hands-on experience with modern AI/LLM technologies.
• Practical experience with LLM-based systems: prompt design, RAG architectures, vector search and embeddings, structured output, and evaluation.
• Experience with at least one agentic or LLM framework (e.g. LangChain/LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, OpenAI Agents SDK, Microsoft Agent Framework) and an understanding of what it takes to make agents reliable rather than merely impressive.
• Experience with cloud-native development (Azure preferred; AWS or GCP equally welcome), including containerization (Docker/Kubernetes) and CI/CD.
• Experience designing and working with APIs, data stores, and integration layers (SQL and NoSQL; e.g. PostgreSQL, MongoDB, Azure AI Search, or comparable).
• Experience bridging communication between global teams and navigating cultural differences in professional settings.

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