AI Product Engineer

Casper Studios

3d • Remote

About The Position

We're looking for engineers who are AI-native, have real fundamentals in programming, data, and systems, and have the judgment to get the most out of LLMs - and know where they break. The work spans enterprise document processing, workflow automation, computer vision, and financial research tooling, across finance, healthcare, and enterprise clients. This is a role for someone who ships, owns outcomes, and wants unusual amounts of responsibility early.

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

Nice To Haves

• Depth in one of our core verticals: financial services, healthcare, or enterprise / contact-center AI
• Comfort being client-facing at a senior level
• Fluency in and preference for TypeScript - much of our stack is full TS
• You've built observability for an AI product
• You're plugged into the applied-AI community

Responsibilities

• 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

Benefits

• Full-time or contract depending on the engagement
• Compensation calibrated to your location and seniority - we'll talk comp and align on specifics early

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed