Principal Engineer, AI and Data Platforms - Director

Deutsche Bank • Cary, NC

1d • $170,000 - $255,000 • Hybrid

About The Position

This is an exciting opportunity to play a leading technical role in shaping the next generation of enterprise AI and data platforms on Google Cloud. You will provide hands-on technical leadership across Ada, our AI execution platform, and Vista, our core data platform supporting AI and analytics solutions, tackling complex engineering challenges and helping these capabilities scale and mature. You will bring deep expertise across AI, data, cloud, platform, and reliability engineering to influence technical direction, elevate engineering standards, and build secure, resilient, production-ready solutions. This role is ideal for a deeply technical engineering leader who wants to remain close to the technology while making an impact across multiple engineering teams and critical enterprise platforms.

Requirements

• 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

Nice To Haves

• Ability to combine deep hands-on engineering expertise with technical leadership across AI, data, cloud, platform, software, and reliability engineering, remaining close to code, design, implementation, and production issues while influencing quality across multiple teams
• Strong technical judgment when evaluating complex system designs, implementation approaches, deployment patterns, and production risks
• Effective coaching and mentoring skills, with the ability to raise engineering standards through practical guidance
• Ability to influence engineering quality and alignment across AI, data, cloud, platform, and reliability stakeholders
• Commitment to secure, scalable, reliable, and operable enterprise platform services supporting critical workloads

Responsibilities

• Provide hands-on technical leadership across the 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
• Partner with Ada and Vista engineering teams to align technical decisions and strengthen implementation, platform quality, and production readiness across AI and data services
• Influence engineers and technical stakeholders across AI, data, cloud, platform, software, and reliability disciplines through sound technical judgment and practical contribution
• Coach and mentor engineers across multiple teams while setting expectations for design quality, secure and reliable delivery, operational resilience, and service maturity

Benefits

• A hybrid working model, allowing for in-office / work from home flexibility
• generous vacation, personal and volunteer days
• Employee Resource Groups support an inclusive workplace for everyone and promote community engagement
• Competitive compensation packages including health and wellbeing benefits
• retirement savings plans
• parental leave
• family building benefits
• Educational resources
• matching gift and volunteer programs

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: No Education Listed