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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Job Description Enterprise AI Architect - **Company:** Alvarez and Marsal - **Location:** London, UK - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Machine Learning, Snowflake, IT Architecture, Data Management, Data Pipelines, Databricks - **Published:** June 7, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=1510b6b7263b7562 ## About the Role Do you have experience in Solution architecture?, * Experience across enterprise architecture and solution architecture with exposure to cloud, data, or AI delivery in large organizations. * Strong understanding of how AI solutions are designed, integrated, governed, and deployed at enterprise scale, including security and compliance considerations. * Hands-on familiarity with modern cloud and data platforms (e.g., AWS, Azure), and ecosystem tools (e.g., Snowflake, Databricks, or similar). * Knowledge of GenAI, machine learning, orchestration and automation, data pipelines, APIs, integration patterns, and enterprise security controls. * Ability to define pragmatic technical architectures without being limited to a single platform or vendor; experience evaluating build/buy/partner options. * Proven track record moving AI use cases beyond pilots into resilient, observable, and cost-effective enterprise solutions. * Comfortable operating from strategic target-state design through delivery detail, including patterns, reference architectures, and implementation guidance. * Excellent stakeholder management and communication skills, able to explain complex topics clearly to business and technology leaders. * Experience in regulated, data-heavy, or complex enterprise environments is advantageous ## Description * We are a cross-disciplinary group bringing together enterprise architecture, data platforms, engineering, security, and delivery excellence to help clients design, govern, and scale AI solutions across complex environments. * We partner with senior business and technology leaders to translate strategic outcomes into secure, scalable, and responsible AI capabilities that deliver measurable impact. * Our work spans advisory and hands-on delivery-defining target-state architectures, establishing guardrails and governance, and guiding engineering teams from prototype to production. How you will contribute * Define enterprise AI architecture spanning data, cloud, applications, integration, and security across diverse technology estates. * Design scalable AI solutions using modern AI, machine learning, and GenAI technologies, aligned to business outcomes and value cases. * Translate business problems into practical AI use cases, solution designs, and delivery roadmaps with clear benefits, risks, and dependencies. * Assess current-state platforms and identify data, platform, and integration changes needed to enable AI at scale. * Establish architecture patterns, guardrails, and governance standards for responsible AI adoption, including security, privacy, and model risk controls. * Partner with cloud, data, engineering, security, and business teams to progress AI use cases from prototype to production with robust MLOps/LMMOps practices. * Lead technical decision-making across platforms, vendors, operating models, and delivery approaches, balancing speed, risk, and total cost of ownership. * Advise senior stakeholders on technical trade-offs, risks, interdependencies, and investment choices to inform portfolio and roadmap decisions. * Drive measurable outcomes through automation, productivity improvements, cost reduction, and better use of enterprise data assets. ## Related Videos - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Reference Architecture of AI in the Cloud](https://www.wearedevelopers.com/videos/1613-reference-architecture-of-ai-in-the-cloud) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Got AI ideas but no money? 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