AI Engineer

Role Description

As a AI Engineer, you play a key role in designing and implementing state-of-the-art AI solutions. You are responsible for the entire AI lifecycle - from data ingestion and transformation to building, deploying, and optimizing machine learning models. You work closely with data platform teams and ensure that AI-driven insights translate into tangible business value.

With a strong focus on innovation, scalability, and operational excellence, you stay up to date with the latest AI advancements (e.g., Multiagent-Architectures) and cloud technologies on Microsoft Azure.

Your Responsibilities

- End-to-End AI Development – Build and optimize AI models, covering the entire lifecycle from data ingestion to deployment and operations.

- Machine Learning & Advanced Analytics – Apply statistical and ML concepts to solve business challenges, including predictive analytics, optimization, and NLP.

- Generative AI - Build, integrate and optimize Large Language Models (LLM), including Text-to-Speech (TTS), Speech-to-Text (STT).

- Data Engineering & Pipelines – Ensure data quality by handling ingestion, preparation, and transformation to create a solid foundation for AI use cases.

- AI Deployment & Operations – Implement scalable and production-ready AI solutions using cloud-based MLOps best practices.

- AI Innovation – Stay up-to-date with the latest advancements in AI and cloud technologies, and evaluate their potential for integration.

- Customer Enablement & Integration – Collaborate with cross-functional teams to customize AI tools and embed them into business processes for maximized value.

- Compliance & Governance - Ensure compliance with data privacy, security, and ethical AI guidelines in all solutions.

Main Requirements

- 3+ years of experience - AI engineering, data science, or machine learning, ideally with data engineering expertise.

- End-to-end AI expertise – Expertise in data preparation, feature engineering, model training, deployment, and continuous optimization.

- Strong Python skills – Proficient in ML frameworks and cloud-based AI platforms like Azure ML and Databricks.

- Cloud & AI ecosystem knowledge – Familiar with Microsoft Azure Data & AI services and leading AI platforms/APIs such as OpenAI, Gemini, and Anthropic.

- MLOps & production deployment – Hands-on experience with MLOps tooling (Azure DevOps, GitHub, GitLab) and deploying AI solutions in production.

- AI infrastructure expertise – Skilled in designing and deploying AI infrastructure, including containerization with Docker.

- Broad AI/ML understanding – Strong foundation in NLP, computer vision, and conversational AI (e.g., Azure Bot Services, Microsoft Copilot).

- Experience with AI models – Familiar with LLMs, TTS, and STT technologies.

- Awareness of AI regulations – Understanding of data privacy regulations (e.g., GDPR) and their implications for AI projects.

- Customer interaction & leadership – Comfortable engaging with stakeholders and leading workshops.

- Innovative & team-oriented mindset – Passion for AI, proactive attitude, and collaborative work style.

- Excellent communication skills – Fluent in English (C2)

Perks

- Why Join Us?

- State-of-the-Art Technologies → Work with Azure, Databricks, and leading cloud technologies on innovative Data & AI projects

- High Performance & Ambition → We are looking for driven professionals who want to make an impact

- Steep Learning Curve & Development Opportunities → Benefit from regular training, certifications, and exciting projects

- Innovative Company Culture → We foster a hands-on mentality, team spirit, and data-driven excellence