Senior Manager of Applied AI Engineering
Cravath Swaine · New York, NY, US
About this role
## Senior Manager of Applied AI Engineering ### Overview The Senior Manager, Applied AI Engineering will play a key leadership role in establishing and growing the Firm's Applied AI Engineering function. This position helps shape how Cravath develops and deploys innovative AI solutions that enhance legal workflows, improve business operations, and create meaningful value across the Firm. You will lead a team responsible for designing, developing, and delivering AI-powered applications, intelligent workflows, automations, and integrations—combining hands-on technical expertise with strong leadership and product thinking to translate emerging AI capabilities into practical, secure, and scalable solutions. ### Responsibilities - Build and lead the Applied AI Engineering function, including technical direction, engineering standards, development practices, and long-term capabilities - Manage, mentor, and develop a growing team of engineers and technical specialists - Partner with PMO, Innovation, legal practices, business stakeholders, and other IT teams to identify/evaluate AI opportunities, assess feasibility, develop solution concepts, and contribute to the AI roadmap and prioritization - Lead architecture, design, development, and deployment of AI-enabled applications, agentic workflows, automations, and integrations - Stay hands-on with technical discovery, prototyping, architecture, code review, and complex engineering problem-solving - Develop reusable AI services, integration capabilities, evaluation frameworks, and engineering patterns to accelerate delivery across the Firm - Evaluate emerging AI technologies, models, platforms, and approaches; recommend build/integrate/extend opportunities based on business value, feasibility, and risk - Collaborate with Information Security, Enterprise Applications, Data Engineering, Infrastructure, and other technology teams to ensure secure, reliable, maintainable integrations - Establish practices for AI quality, testing, monitoring, performance, cost management, and responsible use (including human oversight and safeguards) - Guide the AI solution lifecycle from development through production deployment, ongoing enhancement, and support—working with business and IT stakeholders on long-term ownership/operations - Foster a culture of innovation, collaboration, experimentation, and continuous improvement while maintaining engineering discipline - Perform additional duties and special projects as assigned ### Qualifications - 7–10+ years of hands-on experience in software engineering, solution architecture, or related disciplines in large enterprise environments - 3+ years managing software engineers and leading complex technical initiatives - 1–2+ years building and deploying production AI-enabled applications, including generative AI, retrieval-augmented generation, AI agents, and related technologies - Strong hands-on engineering background (e.g., Python or comparable languages), APIs, cloud platforms, databases, enterprise integrations, and modern software development practices - Proven ability to lead and mentor technical professionals, manage competing priorities, and deliver complex solutions with multidisciplinary teams - Product-oriented thinking and ability to translate business needs into practical technical solutions - Understanding of enterprise security, data privacy, AI governance, and challenges of deploying AI with sensitive information - Excellent communication and interper
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