GCP AI/ML Ops Lead & Production Data Engineer

Charles Schwab; Phoenix (AZ); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

401(k) with company match

Paid time off and sabbatical program

Parental leave and family benefits

Tuition reimbursement

Health, dental, and vision insurance

Job summary

Charles Schwab in Phoenix, AZ, is seeking a hands-on technical lead to drive AI/ML initiatives from development to production on Google Cloud Platform. You will own architecture, deployment, and operations, mentoring engineers and aligning with data scientists and Ops teams.

In this role you will design secure, scalable AI/ML solutions on GCP, lead end-to-end deployments, and champion reliable, cost-conscious platform practices while hands-on coding and delivering with the team.

Qualifications

• 8+ years in data/software engineering with leadership experience.
• Proven AI/ML production deployments on GCP or cloud providers.
• Experience building scalable batch/streaming pipelines.
• Mentoring data engineers and collaborating with data scientists/Ops.

Responsibilities

• Design and build production-ready AI/ML use cases on GCP with security considerations.
• Lead end-to-end deployment from prototype to production with quality gates.
• Document debt and drive resolution across platforms.
• Implement standards, data quality checks, and alerting runbooks.
• Ensure platform reliability, security, and cost efficiency.
• Mentor MLOps and data engineers while contributing code.

Skills

GCP AI/ML

Python

SQL

CI/CD

Docker

Security

Observability

MLOps

Tools

BigQuery

Vertex AI

GCS

Dataflow

Pub/Sub

Cloud Run/GKE

Composer/Airflow

IAM

Cloud Monitoring

Job description

Charles Schwab in Phoenix, AZ, is seeking a hands-on technical lead to drive AI/ML initiatives from development to production on Google Cloud Platform. You will own architecture, deployment, and operations, mentoring engineers and aligning with data scientists and Ops teams.

In this role you will design secure, scalable AI/ML solutions on GCP, lead end-to-end deployments, and champion reliable, cost-conscious platform practices while hands-on coding and delivering with the team.