AI & Multi-Cloud Architecture Lead

Responsible for defining and advancing a cloud-agnostic, AI-enabled architecture strategy that supports enterprise analytics, automation, and operational decision-making across multi-cloud environments. This role leads architecture standards and governance across AWS and Google Cloud Platform while actively delivering hands-on prototypes, data pipelines, and AI integrations to accelerate adoption.

Operating as a shared services architecture function, this role both guides and demonstrates best practices bridging strategy and execution to ensure scalable, cost-efficient, and production-ready solutions aligned with ServiceNow CMDB/APM and Apptio models.

Core Role Identity

Dimension

Expectation

Architecture

Defines standards, patterns, governance

Delivery

Builds POCs, pipelines, and AI integrations, Define and implement cloud-agnostic architecture patterns across AWS and Google Cloud Platform

Standardize Google Cloud Platform governance aligned to AWS controls

Establish reusable reference architectures for data, AI, and infrastructure

Promote abstraction via:

Containers (Kubernetes)

APIs

Infrastructure as Code (Terraform)

1. 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

1. AI Integration & MLOps Enablement

Design and implement AI-ready pipelines (structured + unstructured data)

Support:

Model integration into enterprise workflows

MLOps lifecycle enablement (CI/CD, monitoring, governance)

AI tool/vendor evaluation

Mature organization from:

POCs Embedded AI Governed enterprise AI

1. Data Architecture & Integration (CMDB/APM-Aligned)

Architect data flows integrating:

ServiceNow (CMDB/APM)

Apptio (cost transparency)

Jira (delivery data)

7+ years in cloud architecture, data engineering, or infrastructure

Proven experience in multi-cloud environments (AWS + Google Cloud Platform)

Demonstrated ability to:

Design architecture and deliver working solutions

Build data pipelines and integrations

Strong experience with:

Python, SQL

ETL/ELT pipelines

Infrastructure as Code (Terraform preferred)

Containers (Kubernetes)

AI & Modern Architecture Requirements

Hands-on experience with:

AI/ML integration into enterprise pipelines

MLOps or AI lifecycle tooling

Experience evaluating and implementing:

AI platforms

Automation tooling

Preferred Experience

ServiceNow CMDB/APM integration

Apptio (cost allocation / FinOps)

Experience solving:

Cross-system duplication

Data lineage challenges