AI-Driven Litigation Engineer

Socket.dev; Philadelphia (Philadelphia County); On-site; USD 120,000 - 180,000; Full time

Job summary

Socket.dev in Philadelphia seeks a Legal Engineer - Litigation to turn litigation use cases into reliable, governed AI-enabled workflows, designing prompts, agents, and retrieval pipelines for production-ready solutions meeting legal standards.

The ideal candidate blends hands-on generative AI fluency with practical legal knowledge, collaborating with attorneys to ensure accuracy, governance, and risk controls while scaling workflows across the firm.

Qualifications

• J.D. preferred but not required; equivalent legal-technology experience accepted.
• 3-5 years in legal practice, legal tech, or related fields with hands-on AI/build.
• Hands-on AI build experience: prompt engineering, workflow or agent development, and configuring legal AI platforms.
• Familiarity with retrieval-augmented generation concepts and evaluating model outputs.

Responsibilities

• Build and engineer AI-enabled litigation workflows.
• Design, test, and deploy AI workflows, agents, and skills across AI platforms for litigation use cases.
• Develop and maintain prompt libraries, retrieval pipelines, and reusable workflow components with documentation.
• Translate practice requirements into technical specifications and structured solutions.
• Use low-code tools and integrations to extend firm-approved platforms and connect AI workflows to firm systems.
• Build evaluation frameworks and embed human-review checkpoints and audit mechanisms.

Skills

AI workflow development

Prompt engineering

Low-code tools

Python

Communication skills

Litigation workflow knowledge

Education

J.D. preferred

Tools

Microsoft Copilot

Harvey

CoCounsel

Claude

Job description

Socket.dev in Philadelphia seeks a Legal Engineer - Litigation to turn litigation use cases into reliable, governed AI-enabled workflows, designing prompts, agents, and retrieval pipelines for production-ready solutions meeting legal standards.

The ideal candidate blends hands-on generative AI fluency with practical legal knowledge, collaborating with attorneys to ensure accuracy, governance, and risk controls while scaling workflows across the firm.