Overview
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, document
Full job description
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.
About the team:
The DepoLive team builds real-time products. We own services such as a real-time speech-to-text pipeline used across many Filevine products, and Depo Copilot, the AI legal assistant that processes deposition data as it streams in. Our systems demand low latency, high availability, and strong observability. Our primary goal is to ship new features fast while keeping deployed versions reliable.
Build features end-to-end: architect, implement on both backend and frontend, deploy, and monitor the running service. Take ownership of our systems. You will be responsible for keeping them healthy, debugging issues as they arise, and finding clever ways to scale them as load grows. Partner with our ML team to operate our state-of-the-art ML infrastructure and pipelines. Review code thoughtfully, mentor other engineers, and help set the bar for platform quality.
At least 6 years of software development experience. Full-stack experience: you have owned architecture decisions, built both frontend and backend, handled deployment and monitoring, and iterated on features over time. Hands-on experience with streaming or queuing systems (Kafka, Kinesis, or similar) under high load is required. Preferred experience with Kubernetes, Terraform, Python, React, and AWS (though we care more about engineering skill than specific tools). A product mindset: you care about the business reason behind what you build and understand how it shapes implementation tradeoffs. Fluent English, since you will present your work at our demo days and collaborate on technical decisions in English. Hybrid model: 2x Office, 3x Home Office
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