• Evaluate AI-generated web traffic and cloud infrastructure forecasts by assessing the accuracy and quality of forecasts and responses using a provided rubric

• Lead the architecture and implementation of GCP Entitlement and Access Control systems, including IAM policies, service account governance, and least-privilege access models • Design and deliver a self-serve Landing Zone framework that enables Platform Engineering teams to provision and manage cloud environments consistently and at scale • Co-lead delivery of a Platform Ops Portal, covering management functions such as environment provisioning, access requests, cost visibility, and operational workflows • Partner with client engineering and security teams to align the access control model with regulatory and compliance requirements in a financial services context • Define and enforce GCP governance guardrails, including organization policies, resource hierarchy design, and VPC Service Controls • Drive technical review, identify gaps, and shape the delivery approach before the project kicks off • Enable internal teams through documentation, runbooks, and knowledge transfer that outlast the engagement

• Design, implement, secure, and manage private and public cloud infrastructure • Collaborate with development leads and architects to ensure cloud-native workloads are deployed according to IT best practices • Collaborate with infrastructure leads and architects to ensure high levels of resilience in all cloud environments • Responsible for overall strategy for moving all applications to cloud-native platforms • Integrate cloud compute environments with traditional data center services • Maintain market awareness of cloud platform alternatives • Provide project leadership for requirements gathering, design, planning, coordination, and implementation • Serve as escalation point for troubleshooting problems, and rapid restoration of production services • Lead project teams and work closely with internal and external customers

• Design, build, and support solutions on GCP , including services such as BigQuery, BigTable, Cloud Run, Cloud Storage, Pub/Sub, Dataflow, Agent Platform (formerly Vertex Ai), and related cloud-native services. • Develop and maintain ETL and data pipeline automation for structured and unstructured data workflows. • Build automation using Python and shell scripting to support workflow execution, data movement, platform integrations, monitoring, and operational tasks. • Support AI/ML and agent-based workloads including model integration, agent workflows, and AI-enabled automation where applicable. • Containerize applications, scripts, services, and workflow components using Docker. • Deploy containerized workloads to cloud-native platforms such as Cloud Run, or other managed GCP runtimes. • Build and maintain CI/CD pipelines for application deployment, infrastructure changes, workflow automation, and data pipeline releases. • Develop and maintain Terraform modules for repeatable GCP infrastructure deployments. • Support and integrate workflow or lab orchestration platforms such as Mendix, NAN, Nextflow, or similar tools. • Collaborate with application teams, data engineers, lab systems teams, and business stakeholders to translate workflow requirements into scalable cloud solutions. • Contribute to best practices around cloud security, logging, monitoring, reliability, automation, and cost optimization.