Applied AI Product Manager: Real-World AI Solutions

Marsh; Austin (TX); Hybrid; USD 140,000 - 200,000; Full time

Job summary

Marsh seeks an Applied AI Product Manager to translate advances in AI into reliable, production-ready products. You’ll work across engineering, design, data, research, and go-to-market teams to identify high-value AI-enabled workflows, prototype experiences, and define quality standards for measurable business impact.

You will define success metrics, own roadmaps, and drive release plans while balancing accuracy, latency, cost, reliability, safety, privacy, and user trust in AI features.

Qualifications

• 2+ years of experience building, shipping, implementing, analyzing, or operating software, data, AI, automation, or technical products.
• Strong product judgment and the ability to turn fuzzy problems into sharp product bets.
• Familiarity with modern AI tools and workflows, including hands-on use of AI assistants, coding agents, or product/research harnesses.

Responsibilities

• Own product strategy, roadmap, and execution for applied AI capabilities across one or more product areas.
• Identify workflows where AI can materially improve speed, quality, decision-making, automation, or user experience.
• Translate ambiguous customer problems into clear product requirements, success metrics, prototypes, and release plans.
• Partner with engineering and AI teams on LLM-powered systems, including prompts, context design, retrieval, tool use, agents, model selection, and product architecture tradeoffs.
• Define and run practical evaluation processes for AI features, including quality rubrics, offline evaluations, regression tests, online metrics, user feedback loops, and human review.

Skills

Product judgment

AI tooling familiarity

Technical product development

Communication

Tools

LLM tooling

APIs

Retrieval systems

Python

Job description

Marsh seeks an Applied AI Product Manager to translate advances in AI into reliable, production-ready products. You’ll work across engineering, design, data, research, and go-to-market teams to identify high-value AI-enabled workflows, prototype experiences, and define quality standards for measurable business impact.

You will define success metrics, own roadmaps, and drive release plans while balancing accuracy, latency, cost, reliability, safety, privacy, and user trust in AI features.