Senior Legal Engineer
EverlawOakland, California, United States$163k – $206kPosted 5 May 2022
Job Description
<p>This role sits at the intersection of legal practice and legal technology and plays an essential role in shaping the future of the product. In this role, you will bring a deep understanding of how attorneys work- their processes, use cases- to set the bar for how legal AI behaves, optimizing system prompts, designing evaluations, and ensuring every output aligns with real-world legal standards. You will be instrumental in measuring and continually improving the substantive accuracy and quality of the legal workflows and output the product produces. </p>
<p>By blending <strong>legal domain expertise, data analysis, and workflow modeling</strong>, you'll help ensure our AI tools are accurate, practical, and user-aligned. This hands-on role involves close collaboration with engineering, product, and design to define AI performance metrics, and requires designing and curating datasets reflecting how legal teams interact with documents.</p>
<h3>Getting started</h3>
<ul>
<li><strong>We want you to feel like part of the team early on!</strong> Our onboarding process will integrate you into the company with informative sessions on our product, policies, processes, and team structure and goals. [And you’ll spend meaningful time getting to know your direct reports and discover what excites and challenges them.]</li>
<li><strong>We’re excited for you to learn, grow, and contribute right away!</strong> We trust that you’ll bring experience and knowledge that will uplift and uplevel the team, but we don’t expect you to know everything on Day 1.</li>
</ul>
<h3>Key Responsibilities...</h3>
<p><strong>Prompt Optimization Workflow Development:</strong></p>
<ul>
<li>Systematically discover and test prompt engineering best practices to ensure the accuracy and reliability of AI outputs trusted by legal teams. </li>
<li>Drive product enhancements by translating legal expertise into features. </li>
<li>Collaborate with Engineering on LLM calls. Review and validate product outputs for quality. </li>
<li>Translate client requests into concrete, testable prompts and evaluation criteria. Draft and iterate on system/developer prompts for AI systems.</li>
</ul>
<p><strong>Benchmark Design and Evaluation: </strong></p>
<ul>
<li>Assess foundational model performance and suitability for various legal tasks.</li>
<li>Collaborate with Product and customers to optimize genAI legal workflows. Develop datasets that accurately model legal tasks (e.g., document review, privilege detection), annotating data for edge cases and variability. </li>
<li>Lead the creation of cutting-edge legal AI evaluations, designing and running rigorous tests to ensure outputs meet the high standards of legal professionals. </li>
<li>Dataset curation and labelling for testing. </li>
</ul>
<p><strong>Data Analysis Evaluation:</strong></p>
<ul>
<li>Build and annotate complex legal datasets and document collections.</li>
<li>Analyze model performance and iteratively improve AI solutions.</li>
<li>Build metrics and reporting pipelines to monitor system quality and workflow performance.</li>
<li>Analyze usage data to gauge effectiveness.</li>
</ul>
<p><strong>Collaboration:</strong></p>
<ul>
<li>Serve as the legal voice of quality, advocating for precision, consistency, and clarity in AI outputs.</li>
<li>Provide domain-specific legal expertise that guides feature development and product roadmap decisions.</li>
<li>Act as the bridge between technical teams and legal domain expertise, translating complex legal concepts into clear product requirements and vice versa.</li>
<li>Share findings with cross-functional stakeholders.</li>
<li>Ideate new products based on your deep understanding of legal teams’ pain points.</li>
<li>Participate in customer calls and feedback sessions.</li>
</ul>
<h3>About you</h3>
<ul>
<li>3+ years of relevant legal experience, JD preferred. </li>
<li>Exceptional written communication and a strong interest in the application of AI in the field of law. </li>
<li>Fa ... (truncated, view full listing at source)
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