GenAI Observability & Ops Lead

SCOR Group; Paris; Hybrid; EUR 90,000 - 130,000; Full time

Job summary

SCOR Group is seeking an AI Operations Lead to hands-on integrate, deploy, and monitor AI systems across enterprise products. You will focus on observability, performance, and cost optimization while collaborating with engineering and product teams to deliver robust AI-enabled applications.

The role requires 5–8 years in software/ML engineering, strong GenAI/ML experience, and expertise with cloud environments, Kubernetes, and MLOps tooling. A Master’s or higher degree is preferred.

Qualifications

• 5–8 years in software/ML engineering.
• Experience with GenAI and ML systems.
• Master’s degree (Ph. D. is a plus).
• Bachelor’s degree plus ASA or similar work experience accepted in place of Master’s degree.
• Certifications on Cloud or Microservices or Kubernetes (CKAD) are plus.

Responsibilities

• Implement and operate integration of AI capabilities into enterprise products following standard patterns.
• Contribute to deployment of Copilots and AI assistants, agentic workflows, and predictive ML services.
• Support delivery squads in integrating AI services into business applications.
• Troubleshoot and resolve integration or runtime issues in production.
• AI Observability & Monitoring: design and implement observability frameworks (logging, tracing, metrics).
• Ensure proper logging and monitoring of AI pipelines; define AI SLAs/SLOs; assist incident management and post-mortems.

Skills

Software/ML engineering

GenAI

ML systems

Cloud environments

Kubernetes

MLOps/LLMOps

Observability

Data pipelines

Distributed systems

RAG/Embeddings

Education

Master’s degree

Bachelor’s degree + ASA

CKAD or cloud certifications

Tools

CKAD

CI/CD pipelines

Job description

SCOR Group is seeking an AI Operations Lead to hands-on integrate, deploy, and monitor AI systems across enterprise products. You will focus on observability, performance, and cost optimization while collaborating with engineering and product teams to deliver robust AI-enabled applications.

The role requires 5–8 years in software/ML engineering, strong GenAI/ML experience, and expertise with cloud environments, Kubernetes, and MLOps tooling. A Master’s or higher degree is preferred.