AI & Data Platform Tech Leader (Hybrid)

Deutsche Bank AG

Weston (NC)

Hybrid

USD 170,000 - 255,000

Full time

3 days ago

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Benefits offered by this job

Hybrid work

Generous vacation

Volunteer days

Health benefits

Retirement plans

Parental leave

Job summary

Deutsche Bank AG in Cary, North Carolina, is seeking a Principal Engineer, AI and Data Platforms to lead hands-on engineering across Ada and Vista, shaping the next generation of enterprise AI and data platforms on Google Cloud. You will guide platform design, reliability, and production readiness while collaborating with multiple engineering teams to deliver secure, scalable solutions.

The role requires deep GCP and AI expertise, experience with large-scale data workflows, and a focus on

Qualifications

Advanced hands-on Google Cloud Platform experience, including GKE and production-grade GCP operations, with experience across Cloud Run, Vertex AI, BigQuery, Pub/Sub, Dataflow, Cloud SQL, Cloud Storage, IAM, Workload Identity, and cloud networking.
Deep AI engineering experience with agentic AI platforms and production AI engineering, including large language model integration, retrieval-augmented generation patterns, AI runtime services, model orchestration, evaluation frameworks, and AI observability.
Strong experience with large-scale data platforms, streaming pipelines, real-time processing, lakehouse patterns, data products, metadata, lineage, and governed data services for AI and analytics.
Advanced platform engineering knowledge spanning Kubernetes, Terraform, GitOps, continuous integration and continuous delivery, internal developer platforms, API platforms, service mesh, event-driven architecture, and reusable platform capabilities.
Deep understanding of distributed systems, microservices, OpenTelemetry, site reliability engineering, DevSecOps, performance engineering, resilience engineering, and production operations.
Proven ability to leverage AI tools to enhance productivity and optimize workflows to solve business problems, while applying critical judgment to ensure the responsible and ethical use of data and AI outputs

Responsibilities

Provide hands-on technical leadership across Ada and Vista engineering teams, guiding design choices, implementation patterns, code quality, reliability practices, and production readiness for complex AI and data platform services.
Work directly with engineers to solve difficult platform engineering problems across AI runtimes, data services, distributed systems, cloud infrastructure, observability, automation, and operational resilience.
Contribute to the design and build of reusable platform services, engineering frameworks, developer tooling, and cloud-native capabilities on Google Cloud.
Improve the scalability, performance, reliability, security, and operability of production services supporting critical AI and data workloads.
Lead deep technical reviews covering system design, implementation approach, deployment patterns, failure modes, incident learning, and service maturity.
Raise engineering standards across multiple teams through practical technical coaching, mentoring, design guidance, and disciplined software engineering practices