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Senior Enterprise Architect-Enterprise ArchitectSegment lead-UK
Job Location:
Monthly Salary:
Posted:
7 June 2026 (30+ days ago)
Posted:
Application Deadline:
4 September 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Role Senior Enterprise Architect
Technology Enterprise Architect/Segment lead
Location UK/Europe
Business Unit STG
Compensation Competitive (including bonus)
Job Description
AI-First Solutioning Human Agent Ways of Working & Large-Scale Modernisation
Your role
This is a senior strategic role within the Enterprise Strategic Architecture practice focused on defining and delivering next-generation digital transformation programs for leading global organisations. The successful candidate will bring together deep technology expertise and strong business acumen to help clients navigate complex large-scale modernisation initiatives. As AI becomes central to how enterprises transform this role is expanding in scope: the architect must be equally comfortable designing cloud-native platforms structuring human and agent collaborative workflows and embedding AI-driven capabilities as first-class components of the overall solution. You will collaborate closely with sales and delivery teams across the full program lifecycle from shaping solutions during presales through to governing technical quality in delivery. You will engage with CDOs CTOs and senior digital leaders at client organisations contribute to industry thinking through published viewpoints and speaking engagements and play an active role in identifying emerging technology opportunities that can be developed into compelling propositions for the market.
Responsibilities .
- Strategic Thinking- Candidate can articulate where AI agents replace human tasks vs. augment them in a $10M transformation context. Can draw a humanagent operating model for a business process showing handoff logic oversight points and accountability chains. Understands that LLM inference is now a line item in program budgets and can estimate it at ROM level for a given use case volume.
- Design Depth- Has personally designed or reviewed an agentic system in production e.g. a multi-step reasoning pipeline an autonomous code review agent or a RAG-powered enterprise knowledge layer. Can explain prompt architecture decisions (system prompt structuring context compression strategies few-shot vs. zero-shot tradeoffs) and how these affect both quality and cost. Understands model selection tradeoffs when to use frontier models vs. fine-tuned smaller models vs. cached completions.
- Token Optimization Fluency-Has operationalised token efficiency at scale structured prompt libraries semantic caching chunk sizing for RAG pipelines output length controls batching strategies. Can model cost-per-transaction for an AI-enabled workflow and present that as part of a business case. Understands how token spend interacts with context window limits across model families (GPT-4o Claude Gemini) and can make architecture trade-offs accordingly.
- Agentic architecture design Multi-agent orchestration tool-use design human in-the-loop checkpoints agent failure modes and recovery
- Human agent workflow design Task decomposition across human and AI agents; escalation paths; accountability mapping in regulated environments
- Expertise in leveraging coding agents GitHub Copilot Claude and similar to accelerate software delivery within a structured governed engineering lifecycle
- Design and governance of automated delivery pipelines using tools such as Harness GitHub Actions ArgoCD and Tekton; trunk-based development progressive delivery and release automation
- Full-stack application development Architecture and delivery of modern full-stack applications; proficiency across frontend frameworks API layers backend services and data tiers at enterprise scale
- Modern CI/CD & delivery pipelines Design and governance of automated delivery pipelines using tools such as Harness GitHub Actions ArgoCD and Tekton; trunk-based development progressive delivery and release automation
- High-scalability integration Architecting event-driven and streaming integration at scale using Apache Kafka and Kafka Streams; asynchronous messaging patterns schema registries and real-time data pipelines across distributed systems
- NoSQL & enterprise data platforms Design of polyglot persistence architectures spanning NoSQL stores (MongoDB Cassandra DynamoDB) enterprise caching layers (Redis Hazelcast Memcached) and search platforms (Elasticsearch OpenSearch)
- Hyperscaler resilience patterns Building highly available fault-tolerant solutions on AWS Azure and GCP multi-region active/active chaos engineering SRE practices availability zone failover and disaster recovery at cloud scale
- Token economics & LLM costing Prompt compression context window sizing model tier selection cost-per-transaction modelling at enterprise scale
- AI TCO & commercial modelling Inference cost projections build-vs-buy for foundation models ROI framing for AI-augmented delivery
- Digital transformation leadership AI-native program design spanning cloud integration agentic capability layers and responsible AI governance
- Enterprise integration patterns Streaming API event-driven and real-time patterns extending to RAG vector stores embedding services and LLM APIs as first-class integration nodes
- Chief Architect leadership Governing cross-domain architect teams while managing AI risk hallucination mitigation and responsible AI policy at program level
- Multi-cloud architecture (15 yrs) Hybrid IaaS/PaaS multi-az/region IaC automation first DevSecOps K8s orchestration
- Influencing & stakeholder leadership Builds and sustains networks across organisational boundaries through credibility and influence rather than authority; aligns diverse stakeholders engineering business and executive around a shared technology direction and drives teams to deliver outcomes in complex matrixed environments
- CXO communication Articulates at the right level of abstraction and detail from developer to board level
- Influencing & stakeholder leadership Builds and sustains networks across organisational boundaries through credibility and influence rather than authority; aligns diverse stakeholders engineering business and executive around a shared technology direction and drives teams to deliver outcomes in complex matrixed environments
Preferred
- Should be excellent planner when it comes to perform release planning and other delivery planning.
- Should have excellent problem-solving skills
- Responsible for Coaching and mentoring team members
- BFSI/FS Domain exp
Personal
Besides the professional qualifications of the candidates we place great importance in addition to various forms personality profile. These include:
- High analytical skills
- High customer orientation
- High quality awareness
Why Infosys
Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation.
With over four decades of experience in managing the systems and workings of global enterprises we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills expertise and ideas from our innovation ecosystem.
All aspects of employment at Infosys are based on merit competence and performance. We are committed to embracing diversity and creating an inclusive environment for all employees. Infosys is proud to be an equal opportunity employer.
Required Experience:
Senior IC
About Company
Welcome to Infosys Careers for Experienced Professionals As a leading provider of next-generation consulting, technology and outsourcing solutions, we are dedicated to helping organizations in over 46 countries to renew their core and simultaneously innovate into new frontiers. Whilst ... View more
