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Own product areas from customer discovery through launch and measurable outcomes. Partner closely with legal professionals and enterprise stakeholders to understand workflows, define requirements, prioritize roadmaps, and validate prototypes. Collaborate with Engineering, ML, Design, Sales, and Customer Success to build scalable AI-powered legal products, incorporating security, permissions, integrations, governance, and enterprise rollout needs. Use customer evidence and adoption data to distinguish platform opportunities from one-off requests and shape product strategy.

Build backend services and AI systems for legal drafting, review, and search workflows. Model legal knowledge into ontologies, develop retrieval and evaluation infrastructure, test LLM prompts, optimize queries and performance, and deploy solutions with customers. The role also includes occasional frontend work in TypeScript and React, customer collaboration, and end-to-end ownership of product features.

Build backend services, ontology models, retrieval and evaluation systems, and production LLM workflows for legal drafting and review. Own features end to end across PostgreSQL, OpenSearch, graph databases, and AWS, while improving performance and scale. Work directly with law firm customers alongside senior forward deployed engineers, contribute to TypeScript and React interfaces, and translate vague customer problems into data models, retrieval improvements, or software fixes.

Own full sales cycle for large law firms, manage complex multi-stakeholder deals, drive expansion from initial land to multi-year agreements, build executive relationships, craft ROI-driven proposals, and collaborate cross-functionally to influence product and GTM strategy.

Embeds with law-firm customers to identify high-value workflow problems, define measurable outcomes, and translate findings into product requirements. Builds prototypes, automations, configurations, and evaluations using customer data and AI tools; coordinates with Product, Engineering, and ML through delivery; validates solutions with users; and converts recurring needs into reusable product capabilities and playbooks.

Own end-to-end client relationships for a book of B2B SaaS customers: drive adoption, engagement, retention, and expansion of AI-powered contract drafting tools. Lead onboarding, training, large-scale rollouts, and translate customer feedback into product improvements while designing scalable CS processes and tracking health metrics to demonstrate value.

Embed with law-firm customers to discover high-value workflows, define measurable outcomes, test AI feasibility, and translate findings into product requirements. Build prototypes, automations, evaluations, and configurations; collaborate with Product, Engineering, and ML through delivery; validate solutions with users; and identify repeatable patterns that can become scalable product capabilities and playbooks. The role requires strong technical fluency, customer-facing communication, analytical judgment, project delivery discipline, and willingness to travel onsite.

Own end-to-end client relationships for a B2B legaltech SaaS: drive adoption, retention, and expansion of AI-powered workflows; onboard and train lawyers; measure health metrics; surface product feedback; design scalable CS processes; and advocate for customers internally.

Schedule qualified meetings for Account Executives, research entry points at large law firms, manage personalized outreach campaigns using AI-enabled sales tech, handle discovery calls for inbound leads, align with sales and marketing on GTM strategy, run experiments, and meet monthly meeting quotas. Role is in-office in NYC.

Senior backend engineer responsible for designing and implementing new features, scaling and optimizing the platform, improving Postgres and Elasticsearch performance, fine-tuning LLMs, and making architectural decisions. Collaborate with engineering team, take ownership of features, write performant, maintainable code, and help shape product and infrastructure for data-intensive applications (NLP, search, indexing).