Teams at Discernis

Design and improve production AI workflows for legal document intelligence using agentic orchestration, prompt engineering, retrieval, and model post-training. Own LLM evaluation and benchmarking frameworks, structured outputs, self-hosted model serving, inference optimization, and customer deployments. Build reliable, efficient, explainable systems using Python and modern LLM tooling, with emphasis on quality, latency, cost, and reproducibility.

Build and improve a high-performance frontend for legal document review, including document viewing, search, annotations, citation navigation, and AI result verification. Partner with backend and AI engineers through REST APIs, support a scalable component system, and ensure accessibility, performance, consistency, and secure handling of sensitive browser data.

Own the full enterprise sales cycle for AI document intelligence solutions sold to law firms and corporate legal teams. Manage complex, multi-stakeholder deals involving legal, IT, security, procurement, and executive buyers. Build pipelines, conduct discovery, lead demos and proofs of value with sales engineering, navigate security and deployment reviews, maintain accurate forecasts, and provide market feedback to product and leadership.