Artificial Intelligence Engineer

Summary

Broadfield is a global law firm specializing in transactions and litigation, and they are seeking a Legal AI Engineer to develop AI-powered workflows for their attorneys. This role will involve mapping legal frameworks, building custom workflows, and establishing quality standards for AI outputs.

Responsibilities

• Map and structure the firm's playbooks, litigation frameworks, and due diligence processes into reusable knowledge assets
• Build custom workflows, in particular for document-intensive work across practices — from due diligence automation and playbook-based markup review on the transactional side, to discovery analysis, case chronologies, and brief research on the litigation side
• Design the RAG architecture that grounds AI outputs in the firm's proprietary precedents, deal data, and case materials
• Establish the prompt architecture library, guardrails, and quality standards that every subsequent build will draw from, and collaborate with attorneys to define what constitutes good output

Skills

• Hands-on experience building with legal AI tools (Harvey, Legora, or equivalent) or LLM APIs (Anthropic Claude, OpenAI, or equivalent)
• Experience designing and implementing RAG pipelines — chunking strategies, embedding models, and retrieval optimization
• Familiarity with workflow automation frameworks (LangChain, LlamaIndex, or equivalent) for multi-step AI pipeline construction
• Ability to translate unstructured legal documents into structured, machine-readable knowledge assets
• Proficiency with prompt engineering at a production level — system prompt architecture, guardrails, output schema design, edge case handling
• Comfort working with APIs, JSON, Python, or equivalent scripting
• Builder instinct: you measure your tools' success by adoption, not by what you've shipped
• Speed and judgment: you know when to prototype fast and when to get it right
• Communication: you can explain what you built both to a partner and to a machine
• Ownership: you treat the legal operations system as yours
• Experience in a law firm, legal tech company, or professional services firm
• Built AI-powered workflows
• Exposure to transactional or litigation workflows and data privacy, privilege, and confidentiality considerations in AI deployment
• Exceptional recent graduates with genuine technical depth and drive to build

Qualifications

Must Haves

• Hands-on experience building with legal AI tools (Harvey, Legora, or equivalent) or LLM APIs (Anthropic Claude, OpenAI, or equivalent)
• Experience designing and implementing RAG pipelines — chunking strategies, embedding models, and retrieval optimization
• Familiarity with workflow automation frameworks (LangChain, LlamaIndex, or equivalent) for multi-step AI pipeline construction
• Ability to translate unstructured legal documents into structured, machine-readable knowledge assets
• Proficiency with prompt engineering at a production level — system prompt architecture, guardrails, output schema design, edge case handling
• Comfort working with APIs, JSON, Python, or equivalent scripting
• Builder instinct: you measure your tools' success by adoption, not by what you've shipped
• Speed and judgment: you know when to prototype fast and when to get it right
• Communication: you can explain what you built both to a partner and to a machine
• Ownership: you treat the legal operations system as yours

Nice to Haves

• Experience in a law firm, legal tech company, or professional services firm
• Built AI-powered workflows
• Exposure to transactional or litigation workflows and data privacy, privilege, and confidentiality considerations in AI deployment
• Exceptional recent graduates with genuine technical depth and drive to build