Engineering Manager, AI

Job Description: Engineering Manager, Are you passionate about transforming the future of legal research with AI? Join our Global Westlaw Engineering organization and help shape the next generation of intelligent legal research solutions. The Global Westlaw Engineering organization builds and operates the technology that powers Westlaw, the world's leading legal research platform. Our teams develop innovative products and fiduciary-level, AI-based solutions that help legal professionals find trusted answers, uncover insights, and make confident decisions faster. Working across engineering, AI, data, platform, and product disciplines, we deliver secure, scalable, and intelligent experiences for customers around the globe. As an Engineering Manager, you will build and lead a team of software engineers, including Senior and Staff levels, to deliver the full-stack products, AI-enabled features, and services behind Westlaw's next generation of experiences. Your team will build agentic legal research experiences and the retrieval services that ground them in trusted legal content. You will stay close to the technology as a hands-on leader. You will help shape architecture, set engineering standards, and guide your team in building with agentic systems, retrieval-augmented generation (RAG), and large language models (LLMs). You will also champion AI-assisted development as a way of working, so your team can deliver intelligent, trustworthy, and high-performing solutions for legal professionals worldwide. Key Responsibilities Team Management Build and lead a team of software engineers, including Senior and Staff levels, owning hiring, onboarding, performance management, and professional development, with a focus on deep technical ownership. Develop engineers with strong software fundamentals and domain expertise in information retrieval and agentic system design. Foster a culture of empowered ownership in which engineers define problems, make sound technical decisions, and carry work through to reliable production operations. Shift team mindsets and build a culture of continuous learning, helping engineers adopt new tools, practices, and ways of working. Lead by example as a hands-on technical manager, writing and reviewing code, prototyping solutions, and resolving critical production issues. Translate complex technical concepts and trade-offs into clear terms for stakeholders. Technical Leadership Oversee the development of scalable user interfaces, backend services, and RESTful APIs. Drive GenAI and large language model (LLM) integration initiatives. Shape architecture, engineering standards, coding practices, and code review processes. Champion a DevOps-first mindset in which engineers own build, deployment, monitoring, and reliability, supported by automation and CI/CD. Ensure delivery meets both functional and non-functional requirements, including performance, scalability, reliability, security, and maintainability. Embed quality and security into every stage of development, with rigorous testing, secure coding practices, and continuous evaluation of quality. Design and manage cloud-native solutions on AWS. Evaluate and integrate emerging tool protocols (such as MCP) and retrieval patterns, with a clear understanding of production readiness and operational implications. AI-Enabled Engineering Model AI-assisted and agent-driven development as a team norm, and monitor and optimize token consumption to balance productivity, quality, and cost. Lead feature development using AI agents, setting clear practices for task specification, human review of agent-generated code, and accountability for what ships. Apply AI across the engineering lifecycle, including code generation, code review, test automation, and quality evaluation, with guardrails for security, data handling, and responsible use. Define how the team measures the impact of AI and agents on delivery speed, code quality, and defect rates. Strategic Delivery Define and maintain secure engineering processes for the team that builds and delivers our flagship legal research products. Deliver solutions aligned with product roadmaps through incremental delivery, managing dependencies and tracking success metrics. Continuous Learning Stay current with developments in AI, cloud computing, and software engineering, and bring them into the team's practices. Required Qualifications 8+ years of hands-on software engineering experience across front-end and back-end, building scalable web applications, with 3+ years managing engineering teams. A track record of leading teams that ship and operate production-grade full-stack systems at scale, including secure coding practices and reliability, and of staying hands-on through architecture discussions, design decisions, code reviews, and prototyping. Hands-on experience building with LLMs in production or in serious prototypes, such as RAG, prompt and context design, evaluation, or agent workflows, and daily use of AI coding tools (e.g., GitHub Copilot, Cursor, Claude Code). Experience leading, or working hands-on in, a team that builds and uses AI agents, with strong practices for review, quality, and security. Clear understanding of RESTful API design principles, including: resource modeling and URI designcorrect use of HTTP methods and status codesidempotencypagination, filtering, and versioningauthentication and authorizationconsistent error handlingAPI documentation (e.g., OpenAPI/Swagger) Strong proficiency in Python and in designing and building RESTful APIs. Working proficiency in React or a similar modern UI framework (such as Angular or Vue), and experience with TypeScript and Node.js. Strong knowledge of AWS architecture and services, with experience in DevOps, CI/CD pipelines, and infrastructure as code. Success in hiring, coaching, mentoring, and developing engineers, including Senior and Staff levels. Experience partnering with Product, Design, and cross-functional leaders to set strategy and execute against it. Excellent communication skills, with the ability to set clear goals, give direct feedback, and align stakeholders. Comfort operating in a fast-moving, ambiguous environment, making data-driven decisions as priorities evolve. A strategic mindset, with the ability to ensure technical decisions align with business goals. A Bachelor's degree in computer science, engineering, or a related discipline, or equivalent practical experience. Preferred Qualifications Experience shipping AI-driven or agentic systems in production, such as LLM orchestration, RAG and information retrieval, agent frameworks, and tool protocols (e.g., MCP), using LLM APIs (OpenAI, Anthropic) reliably at scale. Experience with agent evaluation, including testing, benchmarking, and monitoring agent behavior. Experience with Python frameworks such as Django, Flask, or FastAPI. Background managing mixed teams of front-end, back-end, and software/AI engineers. A track record of changing team mindsets and helping engineers adopt new tools and ways of working. Exposure to legal or other regulated professional domains. AWS certifications, such as Solutions Architect or DevOps Engineer. #LI-SM2 This posting is for proactive recruitment purposes and may be used to fill current openings or future vacancies within our organization. What’s in it For You? Hybrid Work Model: We’ve adopted a flexible hybrid working environment for our office-based roles while delivering a seamless experience that is digitally and physically connected. Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance. Career Development and Growth: By fosteri