Data Architect

• Build and maintain secure, scalable infrastructure for ML model training, testing, and deployment using open-source tools.
• Create reusable deployment templates that standardize the path to production across teams.
• Translate prototype models into resilient, monitored, and observable production systems.
• Implement guardrails and controls that ensure compliance with internal standards (e.g., SR 11-7, ISO 42001).
• Partner with data scientists to simplify onboarding to platform capabilities.
• Establish CI/CD pipelines with hooks for testing, scanning, and validation of model code and artifacts.
• Serve as a technical lead for cross-functional delivery efforts involving model onboarding and platform integration.

Required Qualifications

• 6+ years of experience in software, data, or ML engineering roles.
• Strong hands-on experience with tools like MLflow, Metaflow, Airflow, or similar orchestration frameworks.
• Production experience with Kubernetes, Docker, and Helm.
• Deep understanding of Python and software engineering best practices.
• Experience implementing CI/CD pipelines and infrastructure-as-code in a cloud or hybrid environment.

Preferred Qualifications

• Experience working in regulated industries or environments with strong risk and compliance expectations.
• Familiarity with open-source model monitoring, drift detection, or lineage tools (e.g., Evidently AI, Feast, LakeFS).
• Hands-on experience serving models using KServe, Ray Serve, or Triton Inference Server.
• Familiarity with enterprise security tools like Trivy, Aqua, or Snyk for code and container scanning.
• Exposure to LLM/RAG architecture or GenAI platform integration