AI Engineer - Agentic Plattform (m/f/x)

Role Overview 

We are looking for a Platform AI Engineer who will design, build, and scale our AI platform capabilities, enabling seamless model development, deployment, monitoring, and lifecycle management across the organization. You will bring together engineering excellence, MLOps best practices, and a product mindset to turn AI into a reliable, secure, and operational capability. 

Responsibilities 

• Design and operate scalable AI/ML platforms, including training, inference, pipelines, and feature stores 

• Automate MLOps workflows (deployment, orchestration, CI/CD, monitoring, observability) 

• Optimize GPU/accelerated environments for high-performance model workloads 

• Build reusable services, APIs, and tooling to boost engineering and data science productivity 

• Ensure security, compliance, governance, and Responsible AI across the full model lifecycle 

• Evaluate and adopt emerging AI technologies to continuously improve the platform 

• Collaborate with cross-functional teams to deliver reliable, scalable AI products 

• Improve cost efficiency and performance of training, experimentation, and inference 

• Perform LLM pre-training, fine-tuning, and evaluation to ensure quality and reliability 

• Design strong prompts, guardrails, and safety filters for secure LLM operation 

• Develop and maintain RAG capabilities for enterprise knowledge access 

• Build AI agents augmented with tools and internal system integrations 

Requirements 

• 5+ years of experience in Machine Learning Engineering, AI Platform Engineering, or MLOps

• Hands-on expertise with AI/ML tooling and orchestration (e.g., Databricks, Azure ML, MLflow, VertexAI, Kubeflow, Airflow)

• Strong software engineering background in Python (and ideally Java/Go); experience building reliable services/APIs

• Deep knowledge of cloud native architectures (Azure / AWS / GCP), including containerisation (Docker, Kubernetes) and Infrastructure-as-Code

• Experience with GPU/accelerated infrastructure, model optimization, and high-performance workloads

• Familiarity with monitoring and managing production models (drift detection, lineage, model registry, A/B testing)

• Solid understanding of data architecture + integration with data platforms

• Strong communication skills, able to partner with cross-functional teams and translate platform needs into technical solutions

• Fluency in English (additional regional languages a plus)