Data Architect

Job Summary:

The Data Architect will be responsible for building and maintaining secure, scalable infrastructure to support machine learning model development and deployment.

This role involves translating prototype models into production-ready systems, establishing CI/CD pipelines, and ensuring compliance with internal standards.

The architect will collaborate with data scientists and lead cross-functional efforts to integrate models into platform environments.

Key Responsibilities:

Build and maintain infrastructure for ML model training, testing, and deployment using open-source tools.

Create reusable deployment templates to standardize production workflows.

Translate prototype models into resilient, monitored, and observable production systems.

Implement guardrails and controls to ensure compliance with standards (e.g., SR 11-7, ISO 42001).

Partner with data scientists to simplify onboarding to platform capabilities.

Establish CI/CD pipelines with integrated testing, scanning, and validation.

Serve as technical lead for model onboarding and platform integration efforts. Required Qualifications:

Minimum 6 years of experience in software, data, or ML engineering roles.

Hands-on experience with orchestration tools such as MLflow, Metaflow, or Airflow.

Production experience with Kubernetes, Docker, and Helm.

Strong proficiency in Python and software engineering best practices.

Experience implementing CI/CD pipelines and infrastructure-as-code in cloud or hybrid environments. Preferred Qualifications:

Experience in regulated industries with strong risk and compliance requirements.

Familiarity with model monitoring and lineage tools (e.g., Evidently AI, Feast, LakeFS).

Experience serving models using KServe, Ray Serve, or Triton Inference Server.

Knowledge of enterprise security tools (e.g., Trivy, Aqua, Snyk).

Exposure to LLM/RAG architecture or GenAI platform integration.

Education: Bachelors Degree