Senior AI Engineer — Agent Platform & Document Intelligence

**About SmartAdvocate** SmartAdvocate is an industry\-leading legal case management platform used by 20,000\+ legal professionals across North America, from solo practitioners to large multi\-office firms. We are embedding advanced AI directly into the core of the platform to automate complex legal workflows, modernize firm operations, and generate deep document intelligence. **What you would be joining** This is not a greenfield AI experiment. SmartAdvocate already runs a suite of AI services in production: document classification and data extraction, medical chronology generation, demand letter drafting, case chat over vectorized case documents, an agent runtime, and an MCP server that lets external AI platforms operate directly against case data. Your work is the next layer: an agent platform that runs case work autonomously in the background, and document intelligence that lets a generated legal document point back to the exact line of the exact record it came from. **Position overview** We are looking for a hands\-on senior engineer to build two things that reinforce each other: background AI agents that do real case work inside our platform, and generative document engines whose every statement can be traced to its source. This is a build\-and\-operate role. You will design these systems, ship them, and own them in production. **Key responsibilities:** **Autonomous and event\-driven agents** * Architect background AI agents capable of reasoning, decision\-making and multi\-step workflow execution inside the case management system. * Build document intelligence pipelines that extract, summarize, cross\-reference and act on unstructured legal documents — medical records, pleadings, discovery, court orders and correspondence. * Build trigger\-based systems where agents watch case status changes, new documents and incoming data, and fire the right downstream action. * Design the human side of autonomy: work assignable to an agent, a review queue where a supervisor approves or corrects it, escalation when the agent does not know what to do, and feedback that measurably improves the agent next time. * Establish guardrails — permission scoping, approval gates on consequential actions such as sending mail or filing with a court, fallbacks, structured logging and complete auditability. **Generative drafting and visual source attribution** * Build generative synthesis pipelines producing structured legal artifacts: chronological medical summaries, demand letters, case evaluations and discovery drafts. * Implement exact citation linkage that maps generated text back to source document coordinates — page, paragraph and bounding box. * Develop interactive viewer capabilities, or the API payloads behind them, that render hyperlinks inside generated drafts, jump the reader to the precise location in the source PDF, and visually highlight the cited text with its surrounding context. * Write extracted data back into structured case fields with v