Cloud Devops Architect

Job Description

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