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Spellbook

Senior Backend / AI Systems Engineer

Posted 5 Hours Ago
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Remote
Hiring Remotely in Canada
Senior level
Remote
Hiring Remotely in Canada
Senior level
Build and scale backend systems and AI workflows for Spellbook’s legal technology platform. Responsibilities include designing reliable search, inference, orchestration, and RAG retrieval systems; managing rate limits, retries, fallbacks, permissions, and data isolation; optimizing MongoDB performance; partnering with Product and Design; and participating in on-call response. The role requires strong distributed-systems expertise, production backend experience, and the ability to turn ambiguous problems into reliable shipped solutions.
The summary above was generated by AI

Spellbook is the most comprehensive AI copilot for transactional lawyers. It works directly inside Microsoft Word to help legal teams draft, review, and negotiate contracts up to 10x faster and with greater precision. Today, more than 4,000 law firms, in-house teams, and solo practitioners rely on Spellbook to simplify their workflows and eliminate the drudgery of everyday contract work.

We are backed by leading investors including Khosla Ventures, Thomson Reuters Ventures, Inovia Capital, The LegalTech Fund, Bling Capital, and Moxxie Ventures. The company recently raised $50 million in Series B funding, led by Keith Rabois at Khosla Ventures, bringing its total funding to more than $80 million.

*This is an existing vacancy

THE ROLE (BACKEND / AI SYSTEMS ENGINEER)

You’ll build the backend systems that power Spellbook’s product experiences, including both traditional software services and AI-driven workflows. This is a hands-on, high-ownership role for an engineer who cares about product outcomes and understands what requires scale vs what does not, and can turn ambiguity into robust systems that lawyers trust.


THE TECH STACK

Node.js, TypeScript, Express, tRPC, MongoDB, Docker, AWS, CDK, LLM providers (OpenAI, Anthropic, and others)


RESPONSIBILITIES
  • Build and scale backend systems that support core product functionality across Spellbook (Reviews, Chat, Library, and more).

  • Design low-latency, high-reliability search, inference, and orchestration layers for AI features

  • Build and operate RAG retrieval at scale with production-grade performance optimization and permissions-correct data isolation.

  • Own core platform concerns for AI: rate limiting, retries, consistency, fallbacks, safe degradation

  • Partner closely with Product and Design to make good tradeoffs between latency, accuracy, UX, 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


QUALIFICATIONS
  • You have 5+ years of experience building backend systems in production.

  • You have strong fundamentals in backend engineering and distributed systems: APIs, data modeling, concurrency, queues, AI inference

  • You have strong NoSQL (ideally MongoDB) data modeling and performance tuning: schema design/denormalization tradeoffs, indexing strategy, query optimization, and profiling/diagnosing bottlenecks in production.

  • You can take an ambiguous, high-impact problem from “we should do something here” to a clear plan and shipped outcome.

  • You have strong communication skills. You can write and explain technical decisions clearly to engineers and non-engineers.

  • You are a self-starter and problem-solver motivated by curiosity and a desire to help others succeed, encouraged by continuous improvement.

  • You are pragmatic and understand that not everything we ship needs to scale, but know where to draw the line

  • You are a team player who is motivated to help Spellbook succeed. When things break you are eager and able to help fix them. You think of and implement ways to help and improve the work of the team as a whole.


NICE TO HAVES
  • Experience building LLM-powered systems in production, including prompt iteration, tool/function calling, retrieval patterns, and agent orchestration.

  • Experience operating high-scale retrieval systems (vector + lexical search) and measuring/tuning retrieval quality and latency in production.

  • Experience building evaluation frameworks (quality metrics, dataset curation, regression testing).

  • Experience with AWS CDK and operating production services in AWS.


WHY JOIN SPELLBOOK?
  • Embrace autonomy and accountability in a flexible, remote work environment; we focus on outcomes and empower you to determine how to get the job done

  • Access our company-paid group benefits for you and your family, with $1,000 towards mental health support

  • Disconnect during our holiday closure and take advantage of our generous time off policies throughout the year

  • Enjoy monthly paid meals, an annual wellness allowance to support your well-being and parental leave top-ups as your family grows

  • Secure your stake in our success; you’ll receive competitive stock option grants as a pivotal early employee

WHY JOIN SPELLBOOK?
  • Embrace autonomy and accountability in a flexible work environment; we focus on outcomes and empower you to determine how to get the job done

  • Access our company-paid group benefits for you and your family, with $1,000 towards mental health support

  • Disconnect during our holiday closure and take advantage of our generous time off policies throughout the year

  • Enjoy monthly paid meals, an annual wellness allowance to support your well-being and parental leave top-ups as your family grows

  • Secure your stake in our success; you’ll receive competitive stock option grants as a pivotal early employee

Inclusive Hiring at Spellbook

We are committed to creating an inclusive and supportive candidate experience. Should you require any accommodation whatsoever during the interview process, please inform us without any hesitation. Spellbook is dedicated to ensuring equal treatment and opportunity in all phases of recruitment, selection, and employment, in compliance with employment law. We do not discriminate based on gender, race, religion, national origin, ethnicity, disability, gender identity/expression, sexual orientation, veteran or military status, or any other protected category. Spellbook is proud to be an equal opportunity employer, fostering a culture of inclusivity and maintaining a work environment that is free from discrimination, harassment, and retaliation.

Use of Artificial Intelligence in Recruitment

Spellbook uses artificial intelligence (AI) responsibly to support administrative and efficiency-focused aspects of our recruitment process. This includes activities such as drafting job descriptions, generating interview questions, note-taking and recordings, and supporting sourcing and scheduling workflows. All candidate evaluations, interviews, and hiring decisions are made by members of the Spellbook team. While AI tools may assist with screening and assessment, they do not replace human judgment in selection decisions. Our use of AI is intended to streamline routine tasks, improve consistency, and enhance the overall candidate experience. We are committed to upholding principles of fairness, transparency, and accountability in all hiring activities. Spellbook regularly reviews its recruitment practices to mitigate bias and to ensure alignment with applicable laws and evolving best practices.

Our Compensation Philosophy

Spellbook uses industry benchmark data to establish compensation bands for all roles. The salary range listed for a position reflects the expected total wage range for the role—including base salary and on-target commissions, where applicable—and may span multiple career levels. Final compensation is determined during the interview process based on factors such as experience, skills, scope, and role level. In addition to base salary and applicable commissions, total rewards may include equity, health and wellness benefits, and other company programs. Full details will be shared during the interview process.

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