Senior Manager of Applied AI Engineering

Cravath, Swaine & Moore LLP•New York, NY

3d•$190,000 - $230,000•Hybrid

About The Position

The Senior Manager, Applied AI Engineering will establish and grow Cravath’s Applied AI Engineering function, shaping how the Firm develops and deploys AI solutions for legal workflows and business operations. This leader will manage a team responsible for designing, developing, and delivering AI-powered applications, intelligent workflows, automations, and integrations. The role combines hands-on technical expertise, people leadership, and product thinking to turn emerging AI capabilities into practical, secure, and scalable solutions. The position is based in the Firm’s New York office and currently follows a hybrid work schedule, which is subject to change. The estimated salary range is $190,000 to $230,000. Actual compensation will depend on factors including relevant skills, training, experience, education, applicable licensure or certification, market conditions, and Firm factors. The position also includes discretionary bonuses and an employee benefits package.

Requirements

7–10 years of hands-on experience in software engineering, solution architecture, or related technology disciplines in large enterprise environments, including at least 3 years managing software engineers and demonstrated leadership of complex technical initiatives.
At least 1–2 years of experience building and deploying production AI-enabled applications, including generative AI solutions, retrieval-augmented generation, AI agents, and related technologies.
Strong hands-on engineering background, including Python or comparable programming languages, APIs, cloud platforms, databases, enterprise integrations, and modern software development practices.
Ability to lead and mentor technical professionals, manage competing priorities, and deliver complex solutions in collaboration with multidisciplinary teams.
Strong product-oriented thinking, problem-solving skills, and ability to translate business needs into practical technical solutions.
Understanding of enterprise security, data privacy, AI governance, and the challenges of deploying AI with sensitive information.
Excellent communication and interpersonal skills, with ability to work effectively with senior leaders, technical teams, and nontechnical stakeholders.
Bachelor’s degree in computer science, engineering, information systems, or a related field, or equivalent practical experience.
Availability to work additional hours as needed.

Nice To Haves

Experience in a law firm, professional-services organization, or other complex enterprise environment.

Responsibilities

Build and lead the Applied AI Engineering function, establishing its technical direction, engineering standards, development practices, and long-term capabilities.
Manage, mentor, and develop a growing team of engineers and technical specialists.
Partner with the Firm’s PMO, Innovation, legal practices, business stakeholders, and IT teams to identify and evaluate AI opportunities, assess feasibility, develop solution concepts, and contribute to the AI roadmap and project prioritization.
Lead the architecture, design, development, and deployment of AI-enabled applications, agentic workflows, automations, and integrations supporting legal and business operations.
Remain hands-on in technical discovery, prototyping, architecture, code review, and complex engineering challenges while providing team leadership and direction.
Develop reusable AI services, integration capabilities, evaluation frameworks, and engineering patterns.
Evaluate AI technologies, models, platforms, and development approaches, recommending opportunities based on business value, feasibility, and risk.
Collaborate with Information Security, Enterprise Applications, Data Engineering, Infrastructure, and other technology teams to ensure solutions integrate with the Firm’s environment and meet standards for security, confidentiality, reliability, and maintainability.
Establish practices for solution quality, testing, monitoring, performance, cost management, and responsible use, including human oversight and safeguards.
Guide the technical lifecycle of AI solutions from development through production deployment, enhancement, and support, working with business and IT stakeholders on ownership and operational arrangements.
Foster innovation, collaboration, experimentation, and continuous improvement while maintaining engineering discipline.
Perform additional duties and special projects as assigned.