Artificial Intelligence (“AI”) Solutions Engineer

Company: Cooley LLP

Location: New York, NY

Salary: $120,000 - $175,000 a year

Type: Full-time

Posted: 2026-04-10

About this role

Cooley is seeking an Artificial Intelligence (“AI”) Solutions Engineer to join the Practice Engineering team within the Innovation department.

Position summary: As the leading technology law firm, Cooley is determined to become a leader in the digital practice of law. Cooley Innovation embraces a culture of customer service excellence, and all members of the department are expected to move this agenda forward. To that end, under the direction of the Manager of Product Engineering, and collaborating directly with practitioners, technical teams, and innovation stakeholders, the Artificial Intelligence (“AI”) Solutions Engineer leads process automation initiatives by driving prototype-based discovery and building functional workflow demonstrations that validate repeatable, end-to-end processes—from defined inputs through tool orchestration to outputs that meet specified acceptance criteria. This includes developing multi-step automations that combine deterministic scripting with AI workflows, including advanced prompting, retrieval-augmented generation (RAG), and agentic techniques. This role partners across multiple domains including Practice Innovation, Knowledge Management, Software Engineering, as well as resource attorneys and other practitioners across a range of offices and practice areas. Specific duties and responsibilities include, but are not limited to, the following:

Position responsibilities:

  • Responsible for the management, design and development and testing of legal workflow automations, form-building solutions and expert knowledge systems
  • Elicit attorney/practitioner requirements, map end-to-end process steps, define decision points and failure modes, and produce clear acceptance criteria and test cases that make the workflow measurable and reviewable
  • Rapidly build and iterate working proofs-of-concept that validate feasibility of repeatable processes, combining deterministic logic (rules/scripting) with AI steps (prompting, retrieval, ...

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