AI Engineer

About The Company
Norton Rose Fulbright LLP is a distinguished global law firm renowned for delivering comprehensive legal services to a diverse client base that includes some of the world's leading corporations and financial institutions. With a presence in over 50 countries across the United States, Europe, Canada, Latin America, Asia, Australia, Africa, and the Middle East, the firm prides itself on its extensive reach and deep expertise across various sectors. Our commitment to excellence, integrity, and innovation positions us as a trusted partner in navigating complex legal landscapes. We foster a collaborative and inclusive culture that values diversity, promotes professional growth, and encourages pioneering solutions to meet our clients' evolving needs. Our mission is to support our clients with high-quality legal advice while maintaining a sustainable and responsible business model that upholds our core principles of quality, unity, and integrity.
About The Role
We are seeking a highly skilled AI Engineer to join our Legal Innovation, Design & Technology team based in London. This role is instrumental in building our new research and development (R&D) capability focused on creating data-driven and AI-enabled solutions tailored for legal services and the broader legal industry. As part of this innovative team, you will be responsible for developing end-to-end AI capabilities that enhance our legal offerings and internal operations. Your primary focus will be on designing, building, and deploying AI workflows, tools, and integrations that are secure, scalable, and maintainable. You will collaborate closely with the Head of R&D and cross-functional teams to translate product and technical designs into practical, reliable solutions, ensuring that they adhere to enterprise architecture standards, security protocols, and deployment best practices. This is a hands-on, full-stack role requiring a blend of technical expertise and product delivery experience, aimed at transforming innovative concepts into tangible AI products that deliver real value to our clients and internal stakeholders.
Qualifications
The ideal candidate will possess a strong background in AI engineering, software development, and systems integration. A bachelor's or master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field is required. Proven experience in building AI workflows, retrieval systems, and agent-based architectures is essential. Familiarity with programming languages such as Python and TypeScript, along with experience using Docker, Git, and CI/CD pipelines, is necessary. Knowledge of enterprise security standards, data handling, and deployment patterns is also important. Candidates should demonstrate excellent problem-solving skills, the ability to work collaboratively in multidisciplinary teams, and a proactive approach to innovation. Experience working within legal or regulated environments, understanding of AI evaluation and observability, and a strong focus on code quality and testing will be highly valued.
Responsibilities
Develop comprehensive AI-enabled product features, including user interfaces, backend systems, AI orchestration, retrieval mechanisms, and integrations with enterprise systems.
Design and implement agentic AI workflows utilizing structured outputs, tool calling, document processing, human-review steps, and appropriate controls to ensure safety and compliance.
Create reusable agent harnesses that incorporate runtime patterns around tools, state management, context, approvals, and testing fixtures to ensure consistency and safety of AI agents.
Build grounded retrieval and context-aware patterns using approved data sources such as search indexes, document repositories, and permission-aware sources, providing evidence and citations where applicable.
Design and operate evaluation harnesses for AI workflows, including curated test sets, scenario testing, automated and human grading, regression testing, and user feedback loops.
Manage prompts, model configurations, tool schemas, and routing strategies, including fallback mechanisms and optimization for cost and latency.
Implement AI observability through comprehensive traces, logs, metrics, and evaluation results to monitor quality, reliability, failure modes, latency, and costs, facilitating continuous improvement.
Develop clear APIs and integrate AI solutions with approved data, document, search, and business systems to ensure seamless operation.
Create user interfaces that effectively communicate AI outputs, evidence, and controls, enabling users to understand, review, and provide feedback on AI-generated content.
Write maintainable, efficient code in Python and TypeScript, leveraging Docker, Git, automated testing, and CI/CD pipelines to streamline development, testing, and deployment processes.
Work closely with security, authentication, data handling, deployment, and release teams to adhere to firm-wide standards and best practices, ensuring the safety and compliance of AI solutions.
Initial Focus
Develop end-to-end agentic AI features and reusable harnesses for Radar and other designated R&D products.
Establish a practical evaluation and testing framework that enables the team to compare prompts, models, tools, and retrieval approaches both pre- and post-release.
Create grounded AI workflows that integrate firm data, documents, market or regulatory information, and user context into reliable, attributable outputs.
Design interfaces that clearly present AI outputs, confidence levels, supporting evidence, and next steps to legal professionals and business users.
What Success Looks Like
Our R&D products utilize AI workflows grounded in trusted context, with operational observability and user comprehension at the forefront.
AI quality is quantitatively measured, with evaluation results, traces, and user feedback driving continuous enhancements in usefulness and reliability.
AI solutions are seamlessly integrated into existing systems, providing tangible improvements in efficiency, accuracy, and user experience.
The team maintains high standards of security, performance, and maintainability, ensuring AI products are robust and scalable.

Work arrangement
Yes