
2 - 10 employees
Founded 2022
đ¤ Artificial Intelligence
đ˘ Enterprise
đą Media
Artificial Intelligence ⢠Enterprise ⢠Media
Casper Studios is an AI services firm that helps organizations design, build, and embed advanced AI into both external-facing products and internal operations. Their team of product managers, designers, and engineers runs discovery and execution pathways â including use-case validation, rapid prototyping, product & UX design, AI integration engineering, and internal enablement through workshops and automation â to turn AI ideas into production-ready systems. They serve enterprise clients across media & entertainment, financial services, and healthcare, and have built internal products such as Yap (a voice-first AI) and Casper AI (a Chrome extension for summarizing web content). Casper Studios also partners with AI platform providers (e. g. , building with Claude by Anthropic) to integrate modern LLM capabilities into customer workflows.
đĽ 3 hours ago
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2 - 10 employees
Founded 2022
đ¤ Artificial Intelligence
đ˘ Enterprise
đą Media
Artificial Intelligence ⢠Enterprise ⢠Media
Casper Studios is an AI services firm that helps organizations design, build, and embed advanced AI into both external-facing products and internal operations. Their team of product managers, designers, and engineers runs discovery and execution pathways â including use-case validation, rapid prototyping, product & UX design, AI integration engineering, and internal enablement through workshops and automation â to turn AI ideas into production-ready systems. They serve enterprise clients across media & entertainment, financial services, and healthcare, and have built internal products such as Yap (a voice-first AI) and Casper AI (a Chrome extension for summarizing web content). Casper Studios also partners with AI platform providers (e. g. , building with Claude by Anthropic) to integrate modern LLM capabilities into customer workflows.
⢠Own AI product builds end to end, from concept through production, on a client engagement ⢠Decide what to build and how: gather requirements, pressure-test what stakeholders ask for, and prioritize the work that matters ⢠Prototype fast with LLMs, then harden into production with the data pipelines, integrations, and evals that make it trustworthy ⢠Do the data engineering enterprise work requires: ingestion, data modeling, and ETL ⢠Serve as the primary technical contact for clients - talk shop with their engineers and give their executives clarity ⢠Instrument what you build (analytics, funnel metrics, error analysis) and iterate on real usage, not assumptions ⢠Own reliability, security, and cost: auth, secrets, PII handling, and not blowing up the cloud bill ⢠Write up what you learn; for the team, for clients, and publicly
⢠Strong engineering fundamentals: programming, debugging, and system design. You think well beyond the happy path ⢠You've shipped something real with an LLM that got actual usage - ideally with error analysis and evals on your outputs ⢠Data engineering: data modeling and architecture, plus ETL/pipeline experience (Airflow, Dagster, Inngest, Prefect, or similar) ⢠Web and infra fundamentals: auth and web security, profiling slow queries (N+1, unnecessary joins), CI/CD, and cost-aware deployment on a major cloud ⢠You use modern AI tooling (e.g., Claude Code) daily, with customized workflows ⢠High agency: you frame ambiguous problems, state your assumptions, and push work forward without being managed ⢠Strong writing and a high say:do ratio - you can turn a long, meandering client call into a clean set of tickets
⢠Fully remote. We have team members across North America and internationally, mostly overlapping North American time zones. Work when and where you want, as long as the work gets done ⢠Compensation calibrated to your location and seniority - we'll talk comp and align on specifics early
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