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Lead AI Solutions Architect β Legal Operations
Mindlance
πΊπΈ United States
Hybrid
Staff / Principal
3 months ago
$85 β $105 / hour
- ChatGPT
- Copilot
- AI
- Large Language Models
- AI/ML
- Computer Vision
- Natural Language Processing
- MLOps
- AWS
- GCP
- Azure
3 months ago
Key Responsibilities
Remote 37.5 work week
Knows how to build systems with different AI tools (ChatGPT, Copilot)
Requesting BR for 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
- 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
- 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
Lead AI Solutions Architect β Legal Operations Β· Mindlance