MLOps & Agentic Platform Engineer (AI Infrastructure)

Location: San Francisco Bay Area, USA

Department: Engineering

We are seeking a skilled MLOps & Agentic Platform Engineer. This role involves managing model registries, developing continuous training loops, and implementing A/B testing infrastructure. The ideal candidate will have a strong DevOps/MLOps background and be adept at deploying scalable microservices and building observability dashboards.

Responsibilities:

• Manage model registries, continuous training loops, and A/B testing infrastructure.
• Deploy agents as scalable microservices on Kubernetes.
• Build observability dashboards to track token usage, latency, and agent reasoning paths.

Qualifications:

• Strong DevOps/MLOps background (Kubernetes, Docker, Terraform).
• Experience with MLflow, Weights & Biases, or LangSmith.
• Knowledge of building scalable microservice architectures.