Cloud DevOps Lead (AWS+GCP)
Job Location:
West Palm Beach, FL - USA
Monthly Salary:
Posted on:
Vacancies:
Job Summary
Key Responsibilities
1. Multi-Cloud Architecture & Governance
Define and implement cloud-agnostic architecture patterns across AWS and GCP
Standardize GCP governance aligned to AWS controls
Establish reusable reference architectures for data AI and infrastructure
Promote abstraction via:
o Containers (Kubernetes)
o APIs
o Infrastructure as Code (Terraform)
2. Hands-On Enablement (POCs & Pipeline Delivery)
Build proof-of-concept solutions to validate architecture patterns
Develop and optimize data pipelines and integrations across systems (ServiceNow Apptio Jira)
Implement AI-enabled workflows (model integration automation)
Provide hands-on support to delivery teams to accelerate adoption
Translate architecture into working scalable solutions
3. AI Integration & MLOps Enablement
Design and implement AI-ready pipelines (structured unstructured data)
Support:
o Model integration into enterprise workflows
o MLOps lifecycle enablement (CI/CD monitoring governance)
o AI tool/vendor evaluation
Mature organization from:
o POCs Embedded AI Governed enterprise AI
4. Data Architecture & Integration (CMDB/APM-Aligned)
Architect data flows integrating:
o ServiceNow (CMDB/APM)
o Apptio (cost transparency)
o Jira (delivery data)
Address key challenges:
o Data latency
o Data duplication
o Cost visibility gaps
Enforce system-of-record and data ownership principles
5. Governance & FinOps (Advisory Enablement)
Define standards for:
o Cloud cost optimization (FinOps)
o AI governance and lifecycle management
o Data quality and pipeline SLAs
Support KPI transparency:
o Cloud cost per application
o Data pipeline reliability
o AI ROI
Guide teams while enabling them through working solutions
6. Platform Strategy & Shared Services Leadership
Act as a central architecture leader and enabler
Support teams through:
o Architecture reviews
o POC delivery
o Design guidance
Build reusable enterprise assets:
o Patterns
o Templates
o Integration frameworks
Required Experience
7 years in cloud architecture data engineering or infrastructure
Proven experience in multi-cloud environments (AWS GCP)
Demonstrated ability to:
o Design architecture and deliver working solutions
o Build data pipelines and integrations
Strong experience with:
o Python SQL
o ETL/ELT pipelines
o Infrastructure as Code (Terraform preferred)
o Containers (Kubernetes)
AI & Modern Architecture Requirements
Hands-on experience with:
o AI/ML integration into enterprise pipelines
o MLOps or AI lifecycle tooling
Experience evaluating and implementing:
o AI platforms
o Automation tooling
Preferred Experience
ServiceNow CMDB/APM integration
Apptio (cost allocation / FinOps)
Experience solving:
o Cross-system duplication
o Data lineage challenges
Exposure to Generative AI integration
Success Metrics (Aligned to Your KPIs)
Reduction in cloud cost per application
Improvement in pipeline SLAs
Reduction in duplicate data/integrations
Increase in production AI-enabled workflows
Adoption of multi-cloud architecture standards
Number of successful POCs transitioned to production
Required Skills:
AWSMLOPSAIAI-enabled workflowsGCPTerraform
