AI Workflow Engineer/Automation Architect

Modern Family Law

23h•Remote

About The Position

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.

Requirements

Bachelor’s degree or equivalent practical experience in software engineering, computer science, information systems, automation engineering, or related field.
Deep experience in workflow automation, systems integration, software engineering, AI implementation, or automation architecture.
Production-grade Python and using sound software engineering practices, including testing, code reviews, version control, and CI/CD.
Design, build, and optimize AI agent workflows using orchestration frameworks (e.g., LangGraph, LangChain), vector retrieval, LLM Observability platforms (e.g., LangVuse, LangSmith), and API/webhook integrations.
Strong understanding of APIs, workflow orchestration, event-driven systems, and systems integration.
Experience working with automation platforms, orchestration tools, or AI infrastructure frameworks.
Production-grade Python plus solid engineering practices (testing, code review, version control), and agent orchestration frameworks (LangGraph/LangChain, vector retrieval, LLM observability, e.g., LangFuse/LangSmith, API/webhook integrations).
Strong analytical, troubleshooting, and systems-thinking abilities.
Ability to work cross-functionally with technical and non-technical stakeholders.
Excellent organizational and communication skills.
Ability to manage multiple complex projects in fast-moving environments.

Nice To Haves

Experience with generative AI systems and AI orchestration frameworks.
Familiarity with OpenAI, Anthropic, LangChain, LlamaIndex, vector databases, retrieval systems, or workflow automation platforms.
Experience integrating CRM systems, document automation tools, client portals, or SaaS platforms.
Experience within legal technology, healthcare technology, financial services, or other regulated industries.
Familiarity with cloud infrastructure and scalable automation architectures.
Understanding of AI governance, auditability, data security, and confidentiality considerations.
Experience supporting AI-powered conversational systems or agent architectures preferred.

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.