Infrastructure DevOps Lead AI Product Team, AI Transformation Office, EY-Parthenon

Job Title: UK&I Infrastructure / DevOps Lead
Reports To: UK&I SaT Head of Product

Role Type: Permanent FTE

Grade: Level 3 or 4 Assistant Director / Manager or Associate Director / Senior Manager

About the team

The EY-Parthenon UKI AI product team is at a pivotal time for the future of consulting. We are within an enterprise: fast-moving practical commercially aware and disciplined about what we build.

Our remit is to productionise the highest value AI opportunities to translate complex user needs into clear product direction and work with technical teams to deliver products that are trusted adopted and scalable.

This is a hands-on enterprise product role. You will not simply manage a backlog or coordinate delivery. You will understand senior user workflows shape MVPs drive key value & complexity trade-off decisions and move products into real use.

The role

As Infrastructure / DevOps Lead you will own the UKI SaT technical enablement required to move AI products and prototypes from experimentation to scalable deployment. You will work across enterprise technology cloud security architecture infosec product and engineering teams to establish approved environments deployment routes data access patterns and reusable build guidance. This role is for someone who is technically credible pragmatic in complex organisations and motivated by creating repeatable paths for teams to ship safely - not isolated pilots local tools or one-off workarounds.

What you will do

Create and implement the approved enterprise architecture for AI product development

Create and implement approved Azure architecture DevOps tooling and deployment patterns for product and agent development ensuring environments are secure scalable observable and aligned to enterprise architecture requirements.

Own CI/CD and Infrastructure as Code from prototype to production

Own CI/CD and Infrastructure as Code practices to automate environment provisioning security validation and controlled promotion from prototype through to production.

Mobilise approved development environments

Work with Global tech Fabric and enterprise platform teams to establish secure build environments for product and agent development.

Establish safe build patterns for different teams

Define what can be built where by whom using which tools and under which controls so engineers data scientists and approved builders can move faster without creating unmanaged risk.

Enable reusable data and API access

Create scalable approaches for public third-party and internal data integrations reducing duplicated work around authentication access charging governance and support.

Resolve technical constraints that block delivery

Work with Product Managers engineers and Forward Deployed Engineers to diagnose recurring blockers and turn them into clear options recommendations and implementation routes.

Create reusable technical guidance

Document approved architecture patterns deployment pathways environment rules API integration models and DevOps practices so teams can build consistently.

You are

Technically credible

You understand cloud architecture DevOps data platforms integration patterns and AI workflow infrastructure well enough to make practical decisions and challenge assumptions.

Enterprise-minded

You know the goal is not just to make one prototype work. The goal is to create reusable secure and scalable patterns that allow multiple teams to build safely.

Pragmatic and structured

You can balance speed with control break broad technical constraints into root causes options trade-offs decision points and clear next steps.

A strong organisational navigator

You can work across Global technology infrastructure security data architecture product and business teams even where ownership is distributed.

What you definitely need

Experience creating and implementing approved Azure architecture DevOps tooling and deployment patterns for product data or AI development.

Experience owning CI/CD and Infrastructure as Code practices including automated environment provisioning security validation and controlled promotion across environments.

Experience in cloud infrastructure enterprise architecture DevOps platform engineering or technical delivery in a complex organisation.

Strong understanding of cloud platforms ideally Azure and how enterprise environments are governed operated secured and monitored.

Experience working with data platforms APIs authentication models integration patterns and managed service models.

Ability to define architecture patterns that balance speed security scalability observability and maintainability.

Experience working with security infrastructure governance or architecture teams to secure approvals and unblock delivery.

Ability to diagnose technical constraints and translate them into clear recommendations and implementation plans.

Strong stakeholder management and communication skills including the ability to simplify complex technical trade-offs for senior technical and non-technical stakeholders.

A bias to action and comfort making progress where the target architecture or ownership model is still being shaped.

What you might also have

Experience with EY Fabric Databricks Azure DevOps GitHub Kubernetes containerisation or equivalent enterprise DevOps platforms.

Experience supporting AI machine learning data science analytics or automation teams.

Experience with LLM application architecture RAG vector stores orchestration frameworks model APIs or context management.

Experience integrating third-party or public data APIs into enterprise environments.

Experience defining platform operating models developer experience golden paths or paved-road architecture patterns.

Experience in professional services strategy transactions financial services or another complex regulated environment.

What success looks like

Established clear build deployment and environment routes for product and agent development.

Created practical DevOps CI/CD access and API integration patterns that teams can reuse.

Worked with enterprise platform security and architecture teams to unblock priority constraints.

Helped UKI SaT teams move from prototype to tested scalable product with greater speed safety and consistency.

Over time success means UKI SaT has a trusted repeatable technical foundation for AI product and automation development: teams know where to build how to deploy how to access data and APIs and how to scale without reinventing the infrastructure model each time.