Supervisor - Data Operations & Management

Position Overview

We are seeking a highly skilled AI/ML Platform Engineer to design, build, and enhance enterprise AI/ML platform capabilities on Google Cloud Platform (GCP). The role focuses on developing scalable platform services, automation frameworks, governance controls, and self-service capabilities that enable Data Scientists, AI Engineers, and AI/ML Operations teams to efficiently develop and operationalize AI solutions.

Key Responsibilities

Platform Engineering

• Develop and enhance AI/ML platform services leveraging Vertex AI and GCP services.
• Build reusable platform components, templates, accelerators, and SDKs.
• Develop platform APIs, integrations, and automation frameworks.
• Support the implementation of scalable and secure platform architectures.

Platform Enablement

• Build self-service onboarding capabilities for AI engineers and data scientists.
• Create reusable development patterns, standards, and best practices.
• Improve developer experience through automation and tooling.
• Support platform adoption across AI and data teams.

Platform Automation & DevOps

• Develop CI/CD frameworks and automation pipelines for platform services.
• Implement Infrastructure as Code (Terraform) and configuration management practices.
• Maintain source code repositories, testing frameworks, and code quality controls.
• Automate platform provisioning, configuration, and lifecycle management.

Governance & Security

• Implement platform governance controls, access management, and security standards.
• Support auditability, compliance, and platform guardrails.
• Assist in implementing Responsible AI and Agent Governance capabilities.
• Partner with Security and Architecture teams to align platform controls.

Reliability & Observability

• Implement platform monitoring, logging, alerting, and health checks.
• Support platform performance, scalability, and availability improvements.
• Contribute to observability dashboards and operational readiness initiatives.
• Assist with platform capacity planning and resiliency engineering.

Collaboration & Continuous Improvement

• Collaborate with AI/ML Platform Leads, Data Scientists, Data Engineers, and AI/ML Operations teams.
• Participate in platform architecture reviews and engineering improvements.
• Evaluate emerging AI technologies and recommend platform enhancements.
• Contribute to platform documentation, knowledge sharing, and engineering standards.

Qualifications

• 4-7 years of experience in AI/ML Platform Engineering, Cloud Platform Engineering, or Data & AI Platform development, preferably on GCP.
• Strong knowledge of GCP services including Vertex AI, BigQuery, Cloud Storage, Cloud Functions, Cloud Run, and Dataflow.
• Experience developing platform services, automation frameworks, and cloud-native applications.
• Strong programming skills in Python and experience developing APIs and integrations.
• Experience with GitHub, GitHub Actions, pytest, SonarQube, or similar development tools.
• Experience with Infrastructure as Code using Terraform or similar technologies.
• Knowledge of containerization and cloud-native technologies including Docker and Kubernetes.
• Experience with workflow orchestration tools such as Airflow, Astronomer, or similar platforms.
• Understanding of platform security, IAM, access controls, and governance practices.
• Familiarity with platform monitoring, observability, logging, and alerting concepts.
• Experience building reusable templates, accelerators, and self-service capabilities.
• Strong problem-solving, troubleshooting, and collaboration skills.
• Excellent communication skills and ability to work across cross-functional teams.