A hybrid role at Filevine.
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Original listing text, shown exactly as published by the company.
Setup and maintain LLM observability frameworks/tools
Help improve data annotation tooling
Ensure stability of LLM calls (rate limits, provisioned throughput, backups, …)
Help to drive security review processes for AI vendors and providers
LLM cost optimization recommendations (caching, batching, identification of workflow parts causing high costs, etc.)
Hosting finetuned/open weight machine learning models
Helping with LLM evaluations (tooling/framework) with the current main focus on agentic evals
Platform tooling for enabling non-technical people (e.g. PMs) to iterate on prompts
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5+ years building and operating software systems end-to-end
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Hands-on experience with ML infrastructure: model serving, training pipelines, or LLM integrations in production
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Strong understanding of cloud infrastructure and distributed systems (primarily AWS)
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Familiarity with observability tooling and cost management for LLM workloads
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Experience with or openness to: Python, Kubernetes, Terraform
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Thrives in a remote-first, async environment: clear communicator, high ownership, low ego…
Filevine
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Filevine is a legal technology company that provides cloud-based case and practice management software. Their platform helps law firms and legal departments streamline workflows, manage documents, and enhance communication. It is known for modernizing legal operations through automation and an intuitive user experience.
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