Enterprise AI Architect

Linklaters is a people business. Being best in class in the eyes of our clients means that our people must be exceptional.

We respect and value difference but insist on inclusivity.

Role The Enterprise AI Architect is a hands-on technical leader responsible for designing and evolving Linklaters' enterprise AI architecture (spanning generative AI, agentic systems, machine learning, and knowledge-driven platforms) to support the firm's ambition to be a world-leading, AI-powered law firm.

About Linklaters

Linklaters Linklaters is a global law firm, providing legal services in 20 countries and through 30 offices.

We look not only for brilliant minds, but for people who will thrive in our environment: people who love working collaboratively and demonstrate the innovative, efficient, agile, entrepreneurial, and responsible mind-set we aim to bring to every interaction.

Ours is an environment of outperformance.

We achieve this not with targets and incentives, but by fostering a positive, supportive, fair, and open atmosphere.

We celebrate all aspects of diversity and challenge any form of bias.

This is vital to our ability to work as one team, with a common goal.

Responsibilities

• Reporting to the Director of Data, the role sets the technical direction for how AI is built, integrated, governed, and scaled across the firm globally.
• The AI Architect partners with lawyers, business services, engineering, security, and risk teams to design solutions that are secure, explainable, cost-efficient, and aligned with the firm's responsible AI principles.
• Working with the Director of Data, define and execute the firm's AI architecture vision, strategy, and roadmap, aligned with the firm's ambition to be a world-leading, AI-powered law firm.
• Partner with the Director of Architecture, Enterprise Architects, Technology Strategy Lead, and Legal & Risk to shape, align, and secure agreement on the firm's AI strategy and architectural direction.
• Design and maintain the firm's enterprise AI reference architecture, including patterns, standards, guardrails, and blueprints across generative AI, agentic AI, machine learning, and intelligent automation.
• Architect agentic AI systems, including multi-agent orchestration, tool and function calling, human-in-the-loop, Model Context Protocol (MCP) patterns.
• Set standards for LLM selection, routing, and orchestration across foundation models (e.g., Anthropic Claude, OpenAI, Google Gemini, open-source) and legal AI platforms (e.g., Harvey, Legora).
• Define Retrieval-Augmented Generation (RAG) standards, embeddings, vector stores, hybrid retrieval, chunking, and re-ranking, tailored to legal content and knowledge.
• Architect the firm's knowledge graph and context graph capabilities to ground AI in trusted firm data (matters, clients, precedents, know-how) and enable reliable agentic reasoning.
• Establish context engineering standards, including prompt design, system prompts, skills/spec files, grounding, and context window optimisation.
• Own the firm's AI platform blueprint, model/AI gateway, prompt management, evaluation harness, guardrails, observability, and feedback loops, and establish LLMOps and MLOps practices covering deployment, monitoring, drift, and lifecycle management.
• AI solutions are scalable, reliable, secure, maintainable, and cost-efficient, and lead their integration across data platforms (Databricks), business systems, legal applications, and client-facing services.
• Ensure compliance with the firm's data governance, model governance, information security, privacy, and confidentiality obligations, including client guidelines and legal considerations.
• Partner with the Data & AI Design Authority, and Data Council to embed responsible AI principles, fairness, transparency, explainability, and human oversight, into architecture standards.
• Design controls to mitigate AI-specific risks such as prompt injection, data leakage, hallucination and PII exposure, and ensure alignment with emerging regulation (e.g. EU AI Act, NIST, ISO/IEC 42001) Establish AI FinOps patterns, token economics, model routing by cost and quality, caching, and chargeback/showback, to ensure AI investment delivers measurable value.
• Act as the senior technical authority on AI architecture, providing guidance to engineering, data, business, and risk teams, and communicating complex AI concepts clearly to partner-level, C-suite, and non-technical audiences.
• Provide technical leadership and mentoring to AI engineers, data scientists, and architects, fostering a culture of engineering excellence and responsible innovation.
• Research and evaluate emerging AI technologies, models, and frameworks, translating them into reusable architecture patterns, responsible AI principles, and supporting platforms, tools, and frameworks for consistent adoption across the firm.

Requirements

• 10+ years in enterprise architecture, with 3+ years designing and delivering production
• Generative AI and Agentic AI solutions at scale, ideally on Azure (preferred), AWS/ GCP using services such as Azure OpenAI or Vertex AI Deep hands-on expertise with LLM architectures and foundation models (e.g. Anthropic Claude, OpenAI GPT, Google Gemini), including model selection, fine-tuning, distillation, and evaluation.
• Proven experience designing RAG and agentic architectures, vector databases (Azure AI Search, Pinecone), embeddings, hybrid retrieval, multi-agent frameworks (LangGraph, AutoGen, CrewAI), MCP, and other orchestration patterns.
• Strong understanding of knowledge and context graphs (Neo4j, Microsoft GraphRAG, RDF/OWL, ontology design), combined with hands-on LLMOps/MLOps tooling, Model Evaluation and prompt management
• Strong grasp of AI security and Responsible AI, prompt injection defences, guardrails, and alignment with regulatory frameworks.
• Extensive experience as a senior AI or enterprise architect, with a proven track record of designing and delivering production-grade scalable AI solutions, including generative AI, agentic AI, and machine learning, in complex, global, and regulated environments.
• Deep technical credibility across the modern AI stack, LLMs and foundation models, RAG, agentic frameworks, knowledge graphs, LLMOps, and cloud-native AI platforms
• Strong track record leading the full AI architecture lifecycle, from platform selection and reference design through implementation, evaluation, monitoring, and continuous optimisation for scalability, reliability, security, and cost efficiency.
• Well-honed expertise in AI governance and Responsible AI, including model lifecycle management, guardrails, controls, and alignment with regulatory frameworks
• Excellent stakeholder engagement and influencing skills, with the ability to communicate complex AI concepts clearly to partner-level, C-suite, and non-technical audiences, and to drive organisational change in AI adoption
• Solid leadership experience, setting direction, mentoring teams, and fostering a culture of engineering excellence, collaboration, and responsible innovation.

Benefits

• Intellectual curiosity and commercial acumen, leveraging emerging AI technologies and translating them into pragmatic architecture choices, ideally within legal, professional services, or highly regulated industries.
• Private Medical Insurance Free in-house fitness centre and subsidised health club memberships
• Free onsite GP service and periodic health assessments
• Pension and flexible savings options
• Income protection and life assurance
• Electric car and cycle to work schemes
• Emergency family care
• Additional holiday/birthday leave Maternity/paternity/shared parental leave
• Travel insurance and season ticket loan
• Option to join sports and social clubs, as well as our employee networks groups (such as our Gender Equality, With Pride, or Social Mobility Networks) If you think this role would suit you, please click apply below.

Mortgage advice and will-writing services

We look forward to hearing from you!

Technical Skills

Business Analysis, Business Partner Support, Cloud Computing, Disaster Recovery (DR), Enterprise Architecture Strategy, High Availability (Inactive), Innovation Management, IT Architecture Design, Solutions Integration, Systems Analysis, Technology Roadmap This list of duties and responsibilities above is not exhaustive. It is intended to describe the general content of, and requirements for, the performance of this job. As such, the role may also include the undertaking of additional tasks as required.