Hybrid Principal AI & Data Platform Engineer

RiseMe

Weston (NC)

Hybrid

USD 170,000 - 255,000

Full time

4 days ago
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Benefits offered by this job

Hybrid work model
Competitive compensation & benefits
Health and retirement benefits
Educational resources & benefits

Job summary

Deutsche Bank in Cary, NC seeks a Principal Engineer, AI and Data Platforms to lead enterprise AI/data platform efforts on Google Cloud. You will guide Ada and Vista teams, shaping design choices, ensuring production readiness, and advancing platform maturity.

Ideal candidates bring deep AI, data, cloud, and reliability engineering expertise, with a hands-on approach to building scalable, secure production services and mentoring multiple engineering teams in a hybrid work environment.

Qualifications

  • 5+ years of hands-on cloud engineering and platform leadership.
  • Experience delivering enterprise AI/data platforms on Google Cloud.
  • Strong knowledge of reliability, security, and observability practices.

Responsibilities

  • Provide hands-on technical leadership across Ada and Vista teams, guiding design choices and production readiness for AI and data platform services.
  • Collaborate with engineers to solve platform engineering problems across runtimes, data services, cloud infra, and observability.
  • Design and build reusable platform services and cloud-native capabilities on Google Cloud.
  • Improve scalability, performance, reliability, and security of production AI/data workloads.
  • Lead technical reviews on system design, deployment, and service maturity.
  • Raise engineering standards through coaching and disciplined practices.

Skills

Google Cloud Platform
AI/ML leadership
Distributed systems
Reliability engineering
Observability

Tools

Kubernetes
Terraform
GitOps
CI/CD tooling
Vertex AI

Job description

Deutsche Bank in Cary, NC seeks a Principal Engineer, AI and Data Platforms to lead enterprise AI/data platform efforts on Google Cloud. You will guide Ada and Vista teams, shaping design choices, ensuring production readiness, and advancing platform maturity.

Ideal candidates bring deep AI, data, cloud, and reliability engineering expertise, with a hands-on approach to building scalable, secure production services and mentoring multiple engineering teams in a hybrid work environment.

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