Senior LLMOps Engineer
Core
Design, build, and maintain production-grade Large Language Model (LLM) systems in secure hybrid on-prem/cloud infrastructure, focusing on the full LLMOps lifecycle from data preparation to monitoring.
Role type
Senior LLMOps Engineer
Builds
Production-grade LLM systems and ML pipelines
Domain
Enterprise IT / Large Language Models / Cloud Infrastructure
Deliverable
production ML models
Required skills
LLM infrastructure management, container orchestration (Kubernetes, Docker), CI/CD pipeline design, ML model monitoring and evaluation, data versioning, security assessments, Python, Unix/Bash, SQL/NoSQL, messaging platforms (Kafka, RabbitMQ), infrastructure as code (Terraform)
Preferred skills
Experience with big data analytics, non-structured databases, data lakes, MLflow, TensorFlow, Airflow, AWS or EU cloud providers
Technologies
Kubernetes, Docker, Podman, EKS, PKS, MLflow, TensorFlow, Airflow, Kafka, Redis, RabbitMQ, OpenSearch, MongoDB, Terraform, CloudFormation, ELK stack, Prometheus, Grafana, OpenTelemetry, Cloudwatch
Responsibilities
Design and maintain production-grade LLM systems; Deploy, test, and monitor ML models in containerized environments; Develop evaluation frameworks for LLM quality and robustness; Design CI/CD pipelines and orchestration solutions; Create automated anomaly detection systems; Provision security studies and assessments; Support team members on LLMOps practices
Seniority
Senior, 10+ years experience
