Role Purpose

We’re looking for a driven technical leader to take ownership of designing, building, and scaling Stanmore’s enterprise AI and integration platforms. This role is for someone who enjoys shaping direction while staying close to engineering. The successful candidate is someone who can set the architecture, influence the roadmap, and still jump in to build solutions, agents, data pipelines, and integrations when it matters.

You’ll play a key role in defining how AI and automation are applied across both corporate and operational environments, turning ideas into practical systems that lift productivity, strengthen decision-making, and modernise the way we work.

You’ll guide outsourced teams and internal specialists, build strong partnerships across the business, and ensure solutions are secure, scalable, and aligned with Stanmore’s enterprise strategy. If you want to make a meaningful impact on our digital future, this is the role to do it.

Key Responsibilities

AI Architecture, Engineering & Program Delivery

· Design and build AI systems, agentic workflows, agents, and automation solutions using Azure OpenAI, Semantic Kernel, and modern orchestration frameworks.

· Develop hands-on prototypes, POCs, and production-ready AI components.

· Own the technical architecture for all AI initiatives and ensure alignment with business strategy and platform guardrails.

· Produce reusable AI frameworks (prompts, patterns, agent behaviours, integration flows).

· Provide hands-on engineering support across critical phases of design and delivery.

Chair & Lead the AI Center of Excellence (AI CoE)

· Establish and chair the AI CoE as the enterprise authority on AI standards, governance, and prioritisation.

· Lead the AI CoE operating rhythm:

o Technical standards & architecture reviews

o Governance & guardrails

o Use case intake & prioritisation

o Delivery assurance

o Pattern development & knowledge sharing

· Develop and maintain the Stanmore AI Guardrails, including security, ethical AI, privacy, data controls, and responsible AI.

· Ensure all AI work follows a consistent, repeatable, and scalable delivery model.

· Act as the senior spokesperson for AI architecture across the business.

Integration & Data Architecture (Hands-On)

· Lead and contribute to API development, event-driven patterns, and cloud-native integrations across such as SAP, ServiceNow, Ariba, Minestar, and core corporate/operational systems.

· Build reference solutions using Azure Functions, APIM, Data Factory, Event Hub, and Service Bus.

· Define canonical data models, data contracts, and metadata patterns to support AI, reporting, and operational systems.

· Write or support the development of data pipelines, transformation logic, and ingestion frameworks.

Technical Leadership (Lead by Doing)

· Provide hands-on technical leadership through code reviews, pair programming, and building complex components.

· Coach AI engineers, integration developers, and data engineers.

· Set and promote high standards in engineering, DevOps, IaC, observability, and quality practices.

· Ensure architecture decisions are clearly documented, communicated, and adopted.

Delivery & Execution

· Own major architecture artefacts: solution designs, sequence diagrams, models, patterns, operational readiness artefacts.

· Engage with business partners to shape requirements and convert them into actionable technical plans.

· Support delivery squads with hands-on problem solving and technical guidance.

· Ensure solutions meet performance, security, safety, reliability, and cost objectives.

Standards, Governance & Security

· Maintain enterprise-wide AI and integration patterns, guardrails, and architectural blueprints.

· Ensure responsible AI, cyber security, privacy, and data governance are embedded into every solution.

· Publish and maintain documentation on AI standards, decision frameworks, and supported tools.

· Lead formal architecture reviews and provide final technical sign-off on AI-related projects.

Essential Skills & Experience

Required (Hands-On Capability Mandatory)

· Minimum 10 years across architecture/engineering roles with strong hands-on cloud engineering skills.

· Expert-level implementation experience with Microsoft Azure, including:

o Azure OpenAI

o APIM, Functions, Service Bus, Event Grid

o Azure Data Lake, Fabric, Data Factory

o Azure AI Search & vector databases

· Strong engineering ability in: Python, C#, TypeScript, or equivalent languages.

· Proven experience developing agentic AI workflows using Semantic Kernel, Assistants API, LangChain, LlamaIndex, or similar frameworks.

· Extensive integration architecture experience with large enterprise platforms (SAP, ServiceNow, HRIS, mining systems).

· Demonstrated ability to chair governance forums, lead technical standards, and drive enterprise-wide adoption.

· Excellent communication skills with the ability to engage CIO/GM-level stakeholders.

Desirable Skills 

· Azure Architect, Azure AI Engineer, or Data Engineer certifications.

· Experience with MLOps platforms (Azure ML).

· Experience in mining, resources, or operational/asset-intensive industries.

· Familiarity with TOGAF, Agile, or equivalent architecture frameworks.

Role Competencies

· Hands-On Leadership: Leads from the front, diving into technical work when needed.

· Architectural Vision: Understands enterprise priorities, dependencies, and strategic direction.

· Influence & Governance: Able to lead cross-functional groups and enforce technical standards.

· Technical Mastery: Deep skills across AI, cloud, integration, and engineering.

· Strategic Communication: Able to simplify and present complex concepts clearly.

· Delivery Excellence: Balances architectural design with practical execution at speed.

Why Join Us?

· Opportunity to shape the future of mining through cutting-edge data solutions.

· Collaborative and inclusive work environment.

· Competitive compensation and benefits package.

· Commitment to professional growth and sustainability initiatives.