Jobs

Description

Lead AI Solutions Architect – Legal Operations

This is a hands-on AI Architect / AI Engineering role where someone will build AI-powered tools and automation solutions for a legal department.

The person will work directly with attorneys to understand their challenges and then design and build AI applications using tools like ChatGPT, Microsoft Copilot, LLMs, automation platforms, and cloud technologies.

Remote - 37.5 work week

Key Responsibilities

• Knows how to build systems with different AI tools (ChatGPT, Copilot)
• Level 2 (5-9 years) & level 3 (10+ years)
• Potential conversion after 6 months based on performance
• Legal experience is preferred but not required. Heavy focus on tech.

AI & Technology Architecture

• Architect how AI agents, large language models, and automation platforms integrate across our legal workflows
• Directly build internal tools, working side-by-side with attorneys to understand requirements, prototype solutions, iterate based on feedback, and ship production-quality applications
• Own the full engineering lifecycle of internal tools: design, development, testing, deployment, and ongoing maintenance
• Ensure tools comply with data governance, security, and confidentiality requirements
• Monitor tool performance and usage, proactively identifying where systems need to be rethought or rebuilt
• Translate legal requirements into engineering specifications and build solutions that attorneys find intuitive and trust
• Collaborate with IT and Security to ensure tools are properly hosted, secured, and integrated with existing infrastructure

Legal Process Engineering

• Map current legal workflows end-to-end to identify inefficiencies, manual bottlenecks, and automation opportunities
• Redesign processes before deploying technology, fixing the process first, then building the system around it
• Develop and maintain a living operating model for how legal services are designed, staffed, and delivered
• Define what stays in-house, what AI handles, and what goes to outside counsel, and build the workflows to execute that model

Requirements

• Advanced hands-on technical expertise: Demonstrated hands-on expertise in both AI/ML engineering (including LLMs, computer vision, NLP, etc.) and modern full-stack development as an individual contributor.
• Experience with cloud and MLOps: Proficiency with cloud environments (AWS, GCP, Azure) and scaling MLOps for model training, deployment, inference, and monitoring
• Strategic thinking: Ability to develop a long-term technical vision and align it with overall product and business strategy
• Excellent internal and external communication: The ability to communicate complex technical concepts to both technical and non-technical audiences, including executive leadership and partners