AI Workflow Engineer

We’re building the future of legal services.

Modern Family Law (“MFL”) is seeking a highly technical, systems-oriented, and operationally sophisticated AI Workflow Engineer / Automation Architect to help design and implement the next generation of AI-native legal workflows and operational automation systems.

This role is responsible for building the technical “plumbing” that powers AI-enabled legal service delivery, workflow orchestration, client automation systems, and operational integrations across the firm’s technology ecosystem.

The AI Workflow Engineer / Automation Architect will work closely with AI leadership, product teams, attorneys, developers, and operations personnel to architect scalable workflow systems that integrate AI models, internal platforms, document systems, CRMs, client portals, communication systems, and business operations.

This individual will play a critical role in helping MFL evolve into an AI-native legal organization capable of delivering scalable, efficient, compliant, and client-centered legal services.

The ideal candidate combines strong engineering capability with operational systems thinking and a passion for building intelligent workflow infrastructure.

Key Responsibilities

• Design, build, and maintain AI-enabled workflow orchestration systems across legal and operational processes.
• Develop integrations between AI platforms, CRMs, document automation systems, client portals, payment systems, and internal operational tools.
• Build automation pipelines and event-driven workflows that support legal intake, document generation, communication systems, workflow routing, and escalation protocols.
• Collaborate with Legal Knowledge Engineers and Product Managers to translate legal workflows into scalable technical architectures.
• Implement API integrations across third-party platforms and internal systems.
• Develop retrieval, prompt orchestration, and workflow execution systems supporting AI agents and AI-assisted processes.
• Assist in designing scalable architectures for AI-powered client experiences and internal operational systems.
• Monitor workflow reliability, system performance, automation effectiveness, and operational scalability.
• Troubleshoot automation failures, workflow bottlenecks, and integration issues.
• Participate in security, governance, auditability, and compliance planning related to AI workflows.
• Document workflow architectures, system logic, integration maps, and operational standards.
• Evaluate emerging automation technologies, orchestration frameworks, and AI infrastructure tools.