Related skills
mlops langchain llamaindex mlflow kubeflow📋 Description
- Define a multi-year MLOps platform roadmap across training, evaluation, deployment, and monitoring.
- Architect multi-region model inference with data residency and compliance needs.
- Drive model observability and drift detection in partnership with Data Science and Engineering.
- Own vendor and tooling strategy for the MLOps stack; evaluate build vs buy for cost and compliance.
- Publish the Agent Framework Reference Architecture; govern autonomous agents in regulated FinServ.
- Translate emerging agent patterns into concrete product requirements and phased delivery plans.
🎯 Requirements
- 8+ years in product management; at least 3 years in ML infrastructure or MLOps.
- Partner with Data Science/Applied ML and Engineering teams.
- Experience shipping ML platform or AI infra in regulated industries.
- Hands-on with MLOps tooling: MLflow, Kubeflow, SageMaker, Vertex AI, Databricks.
- Knowledge of LLM orchestration frameworks: LangChain, LlamaIndex, AutoGen, CrewAI.
- Experience managing build vs buy decisions or vendor evaluations.
🎁 Benefits
- Bonus
- Private Health Insurance
- Enhanced Assistance Program
- Employee Dental Plan
- Group Life Assurance (GLA)
- Stock options
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