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M

Lead AI Solutions Architect – Legal Operations

Mindlance
πŸ‡ΊπŸ‡Έ United States
Hybrid
Staff / Principal
3 months ago
$85 – $105 / hour
  • ChatGPT
  • Copilot
  • AI
  • Large Language Models
  • AI/ML
  • Computer Vision
  • Natural Language Processing
  • MLOps
  • AWS
  • GCP
  • Azure
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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
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

Lead AI Solutions Architect – Legal Operations Β· Mindlance

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