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Spellbook

AI-powered contract drafting and review

Senior Backend / AI Systems Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • At least 5 years of experience building backend systems in production.
  • Strong fundamentals in backend engineering and distributed systems, including APIs, data modeling, concurrency, queues, and AI inference.
  • Strong NoSQL data modeling and performance-tuning skills, ideally with MongoDB, including schema design and denormalization tradeoffs, indexing strategy, query optimization, and profiling and diagnosing production bottlenecks.
  • Ability to take an ambiguous, high-impact problem from initial idea through a clear plan to a shipped outcome.
  • Ability to write and explain technical decisions clearly to engineers and non-engineers.
  • Motivation to help the team succeed and willingness and ability to help fix things when they break.

Responsibilities

  • Build and scale backend systems supporting core product functionality across Reviews, Chat, Library, and other product areas.
  • Design low-latency, high-reliability search, inference, and orchestration layers for AI features.
  • Build and operate retrieval-augmented generation retrieval at scale, with production-grade performance optimization and permissions-correct data isolation.
  • Own core AI platform concerns, including rate limiting, retries, consistency, fallbacks, and safe degradation.
  • Partner with Product and Design to balance latency, accuracy, user experience, and reliability.
  • Use modern development workflows, including agent-assisted coding, to accelerate delivery while maintaining rigorous review, testing, and security standards.
  • Participate in on-call and incident response as needed, and improve feature reliability in the process.

Desired Qualifications

  • Experience building production LLM-powered systems, including prompt iteration, tool or function calling, retrieval patterns, and agent orchestration.
  • Experience operating high-scale retrieval systems using vector and lexical search, and measuring and tuning retrieval quality and latency in production.
  • Experience building evaluation frameworks, including quality metrics, dataset curation, and regression testing.
  • Experience with AWS CDK and operating production services in AWS.

About the Company

Spellbook

AI-powered contract drafting and review

Spellbook provides AI-powered contract drafting, review, and management inside Microsoft Word for legal teams, automating tasks like missing clauses, inconsistencies, and regulatory checks. It works by embedding AI into the Word drafting flow, with Spellbook analyzing text and suggesting changes, plus Spellbook Associate (an agentic AI) that can plan and execute complex legal tasks autonomously. The company differentiates itself through in-workflow AI within Word, a privacy-first platform with zero data retention, and a scalable agentic AI that handles large-scale legal work. Its goal is to boost legal efficiency and accuracy so lawyers can focus on strategic advice and client service across a global base.

Company size
201-500
Company stage
Debt Financing
Total funding
$122.2M
Headquarters
Toronto, Canada
Founded
2018

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