Job Description

We are undertaking an AI Transformation Assessment to define the strategic, financial, and operational foundations for becoming an AI-Empowered media organisation.


The assessment will evaluate the current state, identify high-value AI use cases across departments, quantify the investment and ROI, and deliver a Business & Investment Case supported by a prioritised Implementation Roadmap.


A multidisciplinary team -- including business, financial, media, and technical experts -- will collaborate with stakeholders to produce actionable insights, establish readiness for AI adoption, and guide the transition toward data-driven, automated, and scalable operations.


We are seeking an Infrastructure & AI Cloud Solution Architect to design, assess, and recommend the scalable, secure, and cost-efficient infrastructure architecture required to support AI workloads across Customer's cloud and on-prem environments. The role ensures the AI Transformation Assessment captures realistic technical dependencies, cost implications, and readiness gaps--bridging strategy and implementation planning.


It will work with the Customer Technology Office to align and re-enforce architecture standards for integration of third-party services; optimising performance and cost-efficiency for the chosen AI platforms and technologies.

Expected Outcomes of this role

A validated

infrastructure assessment

report outlining current capabilities, gaps, and readiness for AI workloads. A proposed

target architecture design

and roadmap supporting the AI Transformation Plan. Cost and effort inputs feeding into the

Business & Investment Case

.

Documented

recommendations and risks

for infrastructure scalability, resilience, and vendor integrations.

Key Duties & Responsibilities:

Design and maintain complex financial models

capturing cost structures, effort estimates, productivity gains, and long-term ROI across multiple departments.

Conduct baseline financial assessments

of current operations, identifying cost inefficiencies and potential automation savings.

Develop scenario projections

(Conservative, Base, Ambitious) that illustrate investment pathways, payback periods, and breakeven points.

Quantify tangible and intangible benefits

, including efficiency gains, risk reduction, workforce redeployment, and audience growth impact.

Consolidate all quantitative findings

into a robust and defensible

Business & Investment Case

, supported by sensitivity and risk analyses.

Partner

with the AI Project Manager, Business Analysts, Technical SMEs, and Department Heads to validate assumptions and align financial outputs with operational realities.

Prepare executive-ready dashboards and summaries

, translating analytical results into actionable insights for decision-makers.

Support Steering Committee presentations

by articulating key financial narratives, trade-offs, and recommendations.

Requirements

10+ years

of experience in infrastructure or cloud architecture.


Hands-on experience working in

data, or digital transformation projects

.


Demonstrated strong expertise in designing

AI/ML-ready environments

, including Cloud GPU/compute orchestration, data pipelines, and storage optimisation.

Strong background in

hybrid cloud architecture

(cloud + on-prem integration) and API-driven ecosystems. Proven ability to translate business and AI requirements into

scalable technical designs and cost-efficient infrastructure solutions

. Excellent understanding of

security, compliance, and data governance

in enterprise AI deployments. Exceptional communication skills, with the ability to collaborate across technical and non-technical stakeholders.

Desirable Qualifications / Skills:

Active

Cloud Certifications

in Microsoft Azure and

AWS

(Professional-Level) Hands on

AWS Cloud Design

and implementation.

Natural Language Processing (NLP):

process queries, and generate human-like text responses - Including Sentiment Analysis applications Experience with

MLOps, DataOps, or automation frameworks

is highly desirable.

Generative AI Expertise:

Experience designing and architecting AI Infrastructure with LLMs, text-to-image/video, and creative AI tools for media workflows.

Data & MLOps:

Strong in ETL pipelines, real-time streaming, and ML lifecycle management architecture design.

Media Infrastructure Knowledge:

Understanding of MAM/DAM systems, metadata, transcoding, and integration of streaming protocols is a plus *

Cloud & GPU Architecture:

Skilled in multi-cloud (AWS/Azure/GCP) and GPU-based AI infrastructure design within Air-Gapped sovereign environments