MLOps Engineer - #2107827

Cognigy

Düsseldorf, North Rhine-Westphalia, Germany Hybrid Germany

Permanent - Full Time

Engineering

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About Cognigy

Cognigy is transforming the customer service industry with the most advanced AI Agent platform for enterprise contact centers. Its award-winning solution, Cognigy.AI, empowers enterprises to deliver instant, hyper-personalized, multilingual service on any channel. By integrating Generative and Conversational AI to create Agentic AI, Cognigy delivers AI Agents that redefine customer experiences, drive satisfaction, and support contact center employees in real-time.

Our skilled #CognigyCrew are the people behind our leading technology and we are now looking for more talented people to join our global team.

Why you’ll love working at Cognigy - Our promise to you

We empower our people to be successful as part of a diverse, passionate and respectful team who are proud to be enabling customer and employee service that is loved by everyone.

We do this by challenging each other to succeed and being enabled to do our best work. Encouraging and supporting growth is at the heart of our success, founded on a culture of mutual respect and trust – always! It’s no wonder that the values that inspire and drive our #CognigyCrew are our 4Ts - Team, Trust, Transparency, Technology.

Your new role – MLOps Engineer

Location: On-site in Düsseldorf or remote in Germany

We are looking for a skilled and ambitious MLOps Engineer to join our Engineering team and take ownership of building and operating scalable, secure infrastructure for Large Language Models (LLMs). You will support our Machine Learning, Product, and SRE teams in deploying and maintaining production-grade AI workloads on Kubernetes using cutting-edge technologies like KubeRay.

You’ll help ensure optimal performance, reliability, observability, and cost-efficiency of Cognigy’s AI infrastructure, automating processes and championing modern MLOps best practices.

Your responsibilities will include

• Build & Operate LLM Infrastructure – Design and maintain scalable LLM-serving systems using Kubernetes and KubeRay.
• Automate & Optimize – Automate deployments, rollbacks, and scaling of LLMs while optimizing resource usage and performance.
• Enhance Observability – Ensure robust monitoring, logging, and alerting for LLM operations (Prometheus, Grafana, etc.).
• Support AI Teams – Empower ML and product engineers with self-service pipelines and scalable infrastructure.
• Prioritize Security – Enforce secure deployments, compliance practices, and robust incident response strategies.
• Improve Documentation – Create and maintain technical documentation to streamline knowledge sharing and onboarding.
• Drive Innovation – Evaluate, adopt, and integrate the latest MLOps and LLM-serving technologies.
• Reduce SRE Toil – Eliminate repetitive tasks and improve operational efficiency across the platform.
  
  

Growth Potential

At Cognigy we are committed to your professional growth. This role offers significant opportunities for career development, including access to ongoing training, and involvement in high-impact projects allowing you to showcase and advance your unique skills and experience.

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