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Alex Hurst

▸ Infrastructure delivery

Ongoing2025 – Present

AI Infrastructure and GPU Cluster Delivery

Senior Director, Technical Program Management & PMO

Delivery outcomes for hyperscale GPU programmes — end-to-end cluster build-out, forecast quality and handover cycle time — delivered under HyperDeploy, the methodology I created and led into adoption.

Context

Hyperscale customers required multi-region GPU infrastructure delivered to aggressive launch timelines, with concurrent builds and clear acceptance paths into production service. Delivery ran under HyperDeploy — the modular, repeatable methodology I created for complex enterprise GPU deployments and led into adoption — inside the delivery organisation described in the PMO Establishment case study. This page covers delivery outcomes and explains HyperDeploy. It does not restate the four-pillar organisational operating model.

Business objective

Deliver contracted infrastructure commitments predictably — protecting critical path, forecast confidence and customer handover — while a further major deployment continues in parallel.

Scale and complexity

  • More than 20,000 GPUs delivered end-to-end across two large clusters
  • A further major deployment led in parallel (in progress)
  • 250K+ contracted GPU portfolio under delivery leadership across EMEA and the United States — contracted scale, not delivered volume
  • Multi-region footprint spanning the UK, Nordics, Southern Europe and North America

Role and accountability

  • Led delivery across the contracted portfolio under programme leadership
  • Created HyperDeploy and led its adoption as the delivery methodology for complex enterprise GPU deployments
  • Owned integrated scheduling, risk, forecasting and executive reporting for delivery streams
  • Led supplier strategy, mobilisation, performance management and delivery recovery
  • Drove operational readiness and handover patterns into production service

Challenge

Run concurrent regional builds with supply, facilities, construction, technical and customer acceptance dependencies without losing schedule integrity or delivery confidence.

Approach and interventions

  • Apply HyperDeploy’s six-stage lifecycle — Qualify, Design, Procure, Build, Deploy and Optimise — with stage gates and readiness/exit criteria
  • Use standardised planning, risk, reporting and delivery artefacts, tailored where programme scale or risk required lighter or fuller controls
  • Maintain integrated plans, dependencies and critical-path visibility across streams
  • Coordinate engineering, suppliers, construction and customer acceptance stakeholders through clear accountability
  • Use portfolio forecasting and variance reviews to intervene early

Governance, planning and coordination

  • Stage gates used as readiness and decision controls — not dates alone
  • Delivery governance, accountability and decision-making across programme streams
  • RAID management and executive reporting through the shared programme platform
  • Defined acceptance criteria and operational readiness before handover

Decisions and trade-offs

  • Treat contracted portfolio scale and delivered volume as distinct facts
  • Invest in repeatable methodology and deployment patterns to improve predictability
  • Develop an acquisition business case for specialist high-density GPU cabling capability where delivery constraints warranted commercial options

Delivery outcome

More than 20,000 GPUs delivered end-to-end across two large clusters, with a further major deployment in progress. Within the wider operating context — including the delivery organisation and HyperDeploy methodology — boots-on-the-ground to customer handover reduced from 14 weeks to 8 weeks for appropriately sized deployments. Approximately 90% delivery-date forecast accuracy within a ±1-week tolerance across six deployments over nine months.

Business and operational significance

Evidence of large-scale AI infrastructure delivery under portfolio leadership, with measurable predictability and shorter handover cycles. The cycle-time improvement is presented as a delivery outcome in that wider operating context — not attributed solely to HyperDeploy.

Related case studies

Delivery methodology

HyperDeploy: A repeatable methodology for hyperscale GPU deployment

Complex GPU infrastructure programmes require more than milestone tracking. They bring together technical design, construction, procurement, suppliers, financial commitments, deployment readiness and customer acceptance.

HyperDeploy is the modular, repeatable delivery methodology I created for complex enterprise GPU deployments, and led into adoption across the portfolio. It structures the deployment lifecycle around defined stages, readiness gates, governance and standardised delivery controls — bringing structure, consistency and control as the portfolio grows.

HyperDeploy is the delivery methodology. The four-pillar model — Squad Delivery, Central Planning, PMO, and Capability & Development — is a separate organisational operating model. The pillars are not stages or components of HyperDeploy.

The lifecycle

  1. 01

    Qualify

  2. 02

    Design

  3. 03

    Procure

  4. 04

    Build

  5. 05

    Deploy

  6. 06

    Optimise

Stage 01

Qualify

Establish whether the opportunity is sufficiently understood and viable to progress into a controlled enterprise deployment.

  • Understand the opportunity and intended outcomes
  • Assess feasibility and significant dependencies
  • Establish the initial business case and commercial context
  • Identify major risks and constraints
  • Establish the initial programme baseline and accountability

Exit gate · Confirm viability, a credible business case and that unresolved issues do not make proceeding untenable.

Stage 02

Design

Turn the qualified opportunity into a sufficiently defined and integrated delivery solution.

  • Develop the technical and solution design
  • Establish the delivery plan and key milestones
  • Develop cost, schedule and baseline assumptions
  • Identify critical dependencies, risks and constraints
  • Establish the design information required for procurement and execution

Exit gate · Confirm the design and delivery baseline are sufficiently developed and approved to support procurement and execution.

Stage 03

Procure

Align procurement and supply-chain readiness with the deployment plan and technical requirements.

  • Coordinate procurement schedules with programme milestones
  • Track supplier commitments and critical dependencies
  • Monitor cost, budget and delivery implications
  • Confirm materials and supply-chain inputs are progressing appropriately
  • Manage risks that could affect the planned build

Exit gate · Confirm required procurement commitments, supply readiness and delivery inputs are sufficiently established to proceed.

Stage 04

Build

Coordinate the construction and technical preparation required to make the deployment ready for customer use.

  • Coordinate construction and infrastructure readiness
  • Manage integrated build plans and milestones
  • Track testing and deployment readiness
  • Resolve technical, supplier and execution dependencies
  • Prepare the deployment and hypercare approach
  • Maintain visibility of risks, changes and decisions

Exit gate · Confirm the deployment is sufficiently built, tested and ready to enter deployment and acceptance.

Stage 05

Deploy

Execute the deployment, validate the delivered solution and achieve customer acceptance.

  • Coordinate deployment execution
  • Track testing and acceptance readiness
  • Resolve defects and technical blockers
  • Manage customer dependencies and acceptance evidence
  • Coordinate transition into agreed support or hypercare arrangements

Exit gate · Confirm acceptance requirements have been met and the solution can transition into agreed operational arrangements.

Stage 06

Optimise

Close the delivery lifecycle responsibly and establish whether the intended outcomes and benefits have been achieved.

  • Confirm benefits and intended outcomes
  • Close remaining programme actions
  • Capture lessons learned
  • Complete appropriate programme closure
  • Use delivery experience to improve future deployments

Exit gate · Confirm the deployment has reached the agreed completion state, with benefits and closure activities appropriately addressed.

Stage-gate approach

The lifecycle is not simply a sequence of dates. Each stage has an exit gate that asks whether the programme is sufficiently ready to progress. Artefacts are developed where they are needed and should reach the required maturity at the relevant gate — making incomplete readiness and unresolved dependencies visible before the programme advances.

Governance and control

  • Programme control

    Maintain an integrated view of scope, milestones, dependencies, risks, issues, decisions, changes and delivery progress.

  • Commercial and financial control

    Connect commercial commitments, programme planning, procurement and financial visibility so delivery decisions reflect the wider business context.

  • Design and engineering

    Keep technical design and engineering readiness connected to the deployment lifecycle rather than as disconnected workstreams.

  • Deployment readiness

    Treat readiness, testing, acceptance and transition as visible parts of the delivery lifecycle.

  • Governance and decisions

    Use appropriate forums for review, escalation and decision-making so material risks and blockers are addressed at the right level.

  • Roles and responsibilities

    Keep ownership clear so programme controls are actionable, not merely reported.

  • Delivery artefacts

    Use standardised planning and control artefacts for a more consistent approach and clearer readiness assessment.

  • Tailoring

    Apply delivery controls proportionate to the needs of the deployment — fuller where risk and complexity demand it, lighter where appropriate.

Standardised delivery artefacts

Categories of delivery information kept consistent across programmes — not proprietary templates or internal checklists.

  • Programme charter and delivery plan
  • RAID and decision records
  • Baseline plan and milestones
  • Cost and budget tracking
  • Procurement schedule
  • Design information
  • Deployment and testing plans
  • Readiness and acceptance evidence
  • Lessons learned and benefits realisation

Why it matters

For large infrastructure deployments, repeatability matters. A consistent methodology provides a common delivery structure while helping teams identify dependencies, manage readiness and maintain control as the portfolio grows.