Senior Software Engineer (Backend)

Filevine is a Legal AI company delivering Legal Operating Intelligence for the future of legal work. Grounded in a singular system of truth, Filevine brings together data, documents, workflows, and teams into one unified platform—where modern legal work happens with clarity and consistency. Powered by LOIS, the Legal Operating Intelligence System, Filevine connects context across every matter to transform legal operations from reactive to proactive. LOIS reads, understands, and reasons across your data to surface insight, automate complexity, and give professionals the clarity and confidence to see more, know more, and do more. Fueled by a team of exceptional collaborators and innovators, Filevine’s rapid growth has earned AI awards and recognition from Deloitte and Inc. as one of the most innovative and fastest-growing technology companies in the country. Role Summary: As a Senior Software Engineer, you’ll own major parts of our AI stack. You’ll prototype zero-to-one workflows, design multi-step and RAG-based pipelines, and push features into production that real attorneys use within days, not quarters. You’ll work across backend, orchestration, retrieval, and product-integrated AI systems. Everything you ship will directly shape how legal teams review, revise, and negotiate contracts inside Word and the browser. Compensation Information: $150,000 - 250,000 base The base salary range represents the low and high end of the salary range for this position. The total compensation package for this position will be determined by each individual’s location, qualifications, education, work experience, skills and performance. We believe in the importance of pay equity - the range listed is just one component of Filevine’s total compensation package for employees. This position is also eligible for a paid time off policy, as well as a comprehensive benefits package. Cool Company Benefits: - A dynamic, rapidly growing company, focused on helping organizations thrive - Medical, Dental, & Vision Insurance (for full-time employees) - Competitive & Fair Pay - Maternity & paternity leave (for full-time employees) - Short & long-term disability - Opportunity to learn from a dedicated leadership team - Top-of-the-line company swag Privacy Policy Notice Filevine will handle your personal information according to what’s outlined in our Privacy Policy. Communication about this opportunity, or any open role at Filevine, will only come from representatives with email addresses using "filevine.com". Other addresses reaching out are not affiliated with Filevine and should not be responded to. Responsibilities Own major product surfaces that rely on retrieval, structured reasoning, and multi-step AI pipelines Prototype, evaluate, and productionize new AI workflows for contract review, clause-level analysis, playbook enforcement, and multi-document tasks Improve our internal LLM orchestration layer, prompt-library, evaluation tooling, and RAG strategies Partner with founders and our in-house legal team to design and validate new features Build backend services that support multi-tenant enterprise customers and high-volume workloads Ship quickly: small PRs, fast iteration cycles, functional releases every week Qualifications 7+ years of engineering experience Strong backend engineering skills and ability to build production systems end to end Experience shipping ML or LLM-powered products at scale Experience with retrieval, embeddings, experimentation, and evals Ability to design multi-step pipelines and agentic workflows Strong instincts around latency, reliability, and fallback strategies Ability to prototype in days and productionize in weeks High standards for correctness, reliability, and UX quality Bonus: Go, Next.js/React, Postgres/pgvector, Cloud Run, multi-provider LLM orchestration What You'll Work On: Designing a multi-step agent that analyzes an entire contract, applies playbooks, generates redlines, and formats them into Word-ready output Improving a retrieval layer that handles 300+ page agreements or mixed corpuses of PDFs, templates, and prior negotiations Building a system that scores clause-level correctness using structured evaluation datasets Creating a streaming, long-running workflow for contract review with checkpoints, retries, and deterministic outputs Designing a prompt-library and golden-file test suite that guarantees consistent outputs across multiple LLM providers

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