Applied AI + NLP Engineer

Entegrata builds governed data platforms for law firms. The Applied AI + NLP Engineer will develop conversational analytics, AI capabilities for structured data, and systems that extract knowledge from legal documents.

Responsibilities:

• Build systems that translate natural language questions into deterministic analytical workflows and governed queries over structured legal data
• Help define and implement semantic models and metadata that enable LLMs and AI agents to reason consistently over operational, business, and legal data
• Improve intent recognition, query planning, and ambiguity resolution to deliver accurate, consistent responses—even when user requests are incomplete or underspecified
• Develop AI agents capable of accessing, interpreting, and synthesizing structured data and legal content to answer complex business questions
• Build orchestration logic that intelligently selects the appropriate data sources, models, tools, and workflows for each request
• Implement guardrails that ensure AI responses align with governed business definitions, semantic models, and firm conventions
• Build evaluation frameworks, benchmark datasets, and automated tests that continuously improve answer quality, determinism, and reliability
• Collaborate with Data Engineering to expose governed metrics, dimensions, relationships, and business logic for AI consumption
• Design and build AI pipelines that transform complex legal documents into structured, machine-understandable data
• Help design and evolve legal data models that capture the key concepts, relationships, and business meaning contained within legal documents
• Develop techniques to identify legal concepts, obligations, timelines, financial terms, parties, and other domain-specific information that populate and enrich those data models
• Design confidence scoring, validation, and human review workflows that improve extraction quality and support continuous model refinement
• Optimize AI workflows for quality, latency, scalability, and cost across the platform
• Partner closely with Product, Data Engineering, and legal domain experts to translate customer needs into production AI capabilities
• Stay current with advances in applied AI, LLMs, and agentic systems, bringing practical innovations into production where they create measurable customer value