AI Product Engineer

Job not on LinkedIn

🕒 July 28

🏈 North America – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 32%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Casper Studios

WebsiteLinkedInAll Job Openings

2 - 10 employees

Founded 2022

🤖 Artificial Intelligence

🏢 Enterprise

📱 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 — including use-case validation, rapid prototyping, product & UX design, AI integration engineering, and internal enablement through workshops and automation — 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.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

• 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