AI Foundation Architect

Why Keyrus, Why Now!

Keyrus is an international group of 2,800 consultants and experts across 28 countries, built on a single conviction:AI does not transform businesses. Architected intelligence does.

For more than 30 years, we have been building the data foundations that make intelligent systems work — designing the Operating System of the intelligent enterprise, where intelligence is embedded into the core of business processes to create sustainable value:we operationalise intelligence.

AI does not replace humans. It repositions us to a place no system can follow:understanding, deciding, designing, and creating.

At Keyrus, you will not just develop skills — you will develop judgment. Your expertise sharpens with every system you architect, every client challenge you solve, and every deployment that compounds on the last.

Over time, you grow into one of the rarest professionals of the intelligence era: someone who bridges data, AI, and human decision-making at scale, across industries and geographies. This is not a role you fill. It is a discipline you master and a story you help write to become aKeyrus Architect of Intelligence.

Technology amplifies. Keyrus culture differentiates. Industrial discipline connects the two.

Role Details

📍Job location: Canary Wharf, London – UK (Hybrid 2–3 days per week in the office)
🕒Contract type: Employee
🗓Target start date: November 2026
⏰Working hours: Full-time
💵Compensation: £90,000–£115,000 gross annual base salary (Senior) or £115,000–£138,000 (Principal) per year, depending on experience and scope

📋 What You'll Architect

At Keyrus, we help organisations transform complexity into measurable outcomes by combining technology, data, intelligence and human decision-making. We bring together deep technical expertise and business understanding to turn AI experimentation into reliable, scalable operational intelligence.

As anAI Foundation Architect, you will help organisations transform complexity into measurable outcomes by combining technology, data, intelligence, and human decision-making.

This role is both technical and consultative — perfect for someone who can combine architecture leadership, hands-on technical depth, and close engagement with client stakeholders. We’re looking for professionals who think like architects and act like builders.

You will define the technical architecture that lets production AI and agentic systems operate reliably at enterprise scale: how models, agents, data, applications, APIs, cloud services, security controls and operational capabilities fit together. You set the principles and boundaries that guide AI Engineers, Software Engineers, Data Engineers and Forward Deployed Engineers, and within your assigned scope you are accountable for the integrity of the target design.

•Define target architectures for production GenAI and agentic systems, connecting models, agents, enterprise data, applications, APIs, cloud infrastructure, security and operational services.

•Establish architecture principles, reference patterns, technical boundaries and non-functional requirements that engineering and delivery teams can apply consistently.

•Make and document material architecture decisions across platform selection, model access, integration patterns, agent execution, data access, deployment, scalability, resilience and observability.

•Review solution and engineering designs for architectural integrity, approving material design decisions within your assigned scope where you are the designated architecture authority.

•Design secure, scalable and operable foundations, ensuring reliability, identity, access, auditability, recovery, maintainability and human-control requirements are considered from the start.

•Own architecture-level AI FinOps, including model and provider routing, consumption patterns, capacity decisions and cost optimisation.

•Guide specialist engineering teams without replacing their ownership, working with AI, Software and Data Engineers, AI Governance specialists and delivery teams on cross-domain decisions.

•Engage with client architecture and technical stakeholders, explaining choices, dependencies, risks, trade-offs and required decisions in clear technical and business terms.

•Convert successful decisions into reusable Keyrus assets, including reference architectures, decision records, standards and design guidance.

👤 Who You Are

•You are an experienced technical architect who combines strategic architecture judgement with recent, practical understanding of production AI systems.

•You move between the complete system and its individual components without trying to own the implementation of every layer.

•You stay close enough to GenAI and agentic engineering to understand how these systems behave in production, not only how they look on a diagram.

•You are credible with engineers and client architects alike.

•You can explain why an architecture decision matters for security, reliability, scalability, performance, cost and long-term operability.

•You know when a decision needs depth and when it needs coordination across specialists.

🛠️ What You Bring

Qualifications & Experience

•Degree in Computer Science, Engineering or a related field, or equivalent professional experience.

•Typically 8+ years designing and owning architecture for complex production technology environments, with clear accountability for cross-system technical decisions.

•Recent practical experience architecting production GenAI, LLM or agentic systems, including how models, data, applications, integrations and infrastructure interact.

•Experience working directly with client architects, engineering leaders, security teams and technical decision-makers.

•Native or bilingual-level English, written and spoken.

Technical & Professional Skills

•Deep architecture expertise in at least one major cloud and AI ecosystem, with the breadth to evaluate comparable technologies and integration approaches.

•Strong understanding of distributed systems, APIs, integration architecture, identity and access, security, scalability, resilience, observability and production operations.

•Data architecture in scope: lakehouse, data mesh, streaming and feature stores.

•Ability to define and communicate reference architectures, technical standards, interface boundaries, non-functional requirements and architecture decision records.

•Strong technical judgement and transparent trade-offs across performance, reliability, security, maintainability, latency, cost and operational complexity.

•Experience architecting RAG, agentic or multi-model systems, including retrieval, model routing, tool access, state, memory, agent execution and human oversight.

•Experience designing model access and deployment patterns across managed AI services, APIs and open-source models.

•Understanding of MLOps / LLMOps, CI/CD, containers, infrastructure automation and monitoring from an architecture perspective.

•Experience conducting architecture reviews and guiding multiple engineering disciplines within a shared target architecture.

•Depth in environments such as Azure AI, AWS Bedrock, GCP Vertex AI, OpenAI, Anthropic, Mistral, Kubernetes, Kafka, Databricks, Snowflake, Apache Iceberg, Palantir Foundry, Terraform, MCP, AI gateways or OpenTelemetry. These are examples, not a checklist.

Nice to Have

•AI agent platform engineering: reusable execution environments, tool gateways, permissions, shared observability and runtime controls.

•Reference implementations or technical spikes to validate critical architecture decisions.

•Enterprise architecture frameworks or formal architecture-governance processes.

•Hybrid, sovereign, regulated or security-sensitive AI environments.

•Complex event-driven, streaming, distributed or high-scale architectures.

•Consulting or client-facing experience, and exposure to international projects or multicultural teams.

⭐ What Makes You Successful

•You make architecture decisions explicit rather than letting them emerge accidentally during implementation.

•You balance technical ambition with production reality, challenge unnecessary complexity and choose patterns teams can build, operate and evolve.

•You know which decisions require architecture authority and which should stay with specialist engineers.

•You use production constraints (security, reliability, latency, cost, scalability, maintainability) to guide design.

•You communicate architectural trade-offs clearly to technical teams and client stakeholders.

•You create reusable architecture knowledge rather than solving every engagement from zero.

🎁 What We Offer at Keyrus UK

• Competitive holiday allowance

• Private Medical & Dental Insurance (Bupa)

• Group Life Insurance

• Gym & fitness discounts viaPluxee (Sodexo)

• On-site gym access at our London office

• Access tolifestyle discounts (travel, retail, entertainment & more) viaPluxee (Sodexo)

• Auto-enrolment pension scheme with Aegon.

• Training & Development via KLX (Keyrus Learning Experience)

• Strong focus oncareer development and internal mobility.

• Electric & hybrid car scheme viaTusker

• Annual discretionary bonus, based on individual and company performance

• Referral bonus for introducing new colleagues.

💰 How Our Salary Ranges Work

At Keyrus, salary ranges reflectdifferent levels of mastery and impact within the same role — not different job titles.

• Bottom of the range
  You meet the core requirements and will need ramp-up time and support.

• Middle of the range
  You are fully autonomous from Day 1 and deliver consistently.

• Top of the range
  You are a reference for the role, mentor others, and raise the bar for the team.

Final offers are based onexperience, autonomy, scope, and market context, and are discussed transparently during the process.

🔒 Responsible AI & Recruitment

At Keyrus, all stages of our recruitment process are conducted and evaluated by human recruiters and interviewers.
To support accuracy and efficiency, AI may occasionally be used internally by our team exclusively fornote-taking purposes during interviews. AI isnever used to make decisions.

To ensurefairness, authenticity, and the protection of confidential and proprietary information, the use of AI tools by candidates during the recruitment process isstrictly prohibited.

Our commitment toresponsible AI practices ensures that hiring decisions are based solely on each candidate’s own skills, experience, judgment, and expertise.

⚠️Any use of AI assistance during the interview process may result in immediate disqualification from the recruitment process.

♿ Equal Opportunity Statement

We are committed to building an inclusive workplace and encourage applications from all backgrounds, regardless of race, ethnicity, gender identity, sexual orientation, age, disability, or any other protected characteristic.