Sr. Software Engineer - GCP - Enterprise Cloud & AI Platform
The GCP Software Engineer is responsible for designing, building, and operating secure, compliant, and scalable cloud and AI-enabled platforms on Google Cloud Platform (GCP). This role enables application, data, and analytics teams by providing standardized cloud infrastructure, Kubernetes platforms, and approved Google AI services, while meeting financial services regulatory, security, and resiliency requirements.
The engineer partners with the Cloud, Data & AI teams, Information Security, and Risk to ensure AI workloads are deployed with appropriate governance, data controls, and observability.
Key Responsibilities
Enterprise Cloud & AI Platform
- Design and maintain enterprise GCP landing zones aligned with governance standards
- Build and operate shared cloud services supporting AI and non-AI workloads
- Implement Infrastructure as Code (Terraform) for platform, networking, and AI service enablement
- Support hybrid connectivity and secure data access patterns for AI use cases
Kubernetes, Containers & AI Workloads
- Engineer and operate GKE clusters for application and AI inference workloads
- Enable containerized AI services and microservices using approved base images
- Support GPU-enabled workloads where approved
- Implement standardized deployment patterns for AI APIs and services
Google AI / GenAI Enablement
- Enable and operate approved Google AI services including Vertex AI, Gemini APIs, and BigQuery ML
- Implement secure access controls, networking, and monitoring for AI services
- Integrate AI platforms with CI/CD pipelines and enterprise SDLC controls
- Partner with Data & AI teams to operationalize workloads safely and compliantly
DevOps, Automation & MLOps Foundations
- Build secure CI/CD pipelines for application and AI workloads
- Support MLOps foundations such as model deployment automation, environment promotion, rollback, monitoring, and logging
- Enforce guardrails, approvals, and policy-as-code for AI usage
Security, Risk & Compliance
- Implement IAM, workload identity, and least-privilege models
- Enforce data residency, encryption, and access policies
- Integrate AI platform telemetry with enterprise logging, monitoring, and SIEM
- Support audits, risk reviews, and regulatory requirements
Required Qualifications
- 5+ years of experience in cloud, platform, or DevOps engineering
- Strong experience with Google Cloud Platform
- Expertise with Terraform
- Experience operating Kubernetes / GKE
- Proficiency in Python, Bash, or Go
- Experience in regulated environments
Preferred Qualifications
- Experience enabling Google AI services
- Familiarity with MLOps
- Experience supporting AI inference workloads
- GCP certifications
