Spellbook
LegalTech
Backend/AISystemsEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Backend / AI Systems Engineer at Spellbook. Skills: Backend systems development, AI-driven workflows, Distributed systems, NoSQL data modeling and performance tuning, LLM-powered systems, RAG retrieval at scale. Build and scale backend systems that support core product functionality. Design low-latency, high-reliability search, inference, and orchestration layers for AI features”
What You'll Achieve.
Build the backend systems that power Spellbook’s product experiences; Turn ambiguity into robust systems that lawyers trust; Accelerate delivery while maintaining rigorous review, testing, and security standards; Improve feature reliability
Industry & Context.
Problem-solver motivated by curiosity; Turning ambiguity into robust systems
Participate in on-call and incident response
What They're Looking For.
Must Have
5+ years of experience building backend systems in production, Fundamentals in backend engineering and distributed systems: APIs, data modeling, concurrency, queues, AI inference, NoSQL (ideally MongoDB) data modeling and performance tuning: schema design/denormalization tradeoffs, indexing strategy, query optimization, and profiling/diagnosing bottlenecks in production, Ability to take an ambiguous, high-impact problem from 'we should do something here' to a clear plan and shipped outcome, Communication skills, Self-starter and problem-solver motivated by curiosity and a desire to help others succeed, encouraged by continuous improvement, Pragmatic understanding of scalability needs, Team player motivated to help Spellbook succeed, Ability to help fix things when they break, Ability to think of and implement ways to help and improve the work of the team as a whole
Nice to Have
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
What You'll Do.
Build and scale backend systems that support core product functionality
high-reliability search
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
Partner closely with Product and Design to make good tradeoffs between latency
Use modern development workflows
including agent-assisted coding
to accelerate delivery while maintaining rigorous review
and security standards
Participate in on-call and incident response as needed
Improve feature reliability
How You'll Work.
Team & Collaboration
Partner closely with Product and Design; Help and improve the work of the team as a whole
Communication Scope
Write and explain technical decisions clearly to engineers and non-engineers
Process & Methodology
Take an ambiguous, high-impact problem from 'we should do something here' to a clear plan and shipped outcome
Full Job Description
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.
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