Company:
Marsh

Description:

Marsh is seeking an Applied AI Product Manager to help translate advances in AI into useful, reliable, production-ready products. This role sits at the intersection of customer discovery, product strategy, technical execution, and responsible deployment. You will partner across engineering, design, data, research, go-to-market, legal, and customer-facing teams to identify high-value workflows, prototype AI-powered experiences, define quality standards, and deliver measurable business and user impact.

We will count on you to:
* 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.
* Make product decisions across accuracy, latency, cost, reliability, safety, privacy, and user trust.
* Use modern AI tools and coding/productivity harnesses to accelerate research, prototyping, analysis, QA, and product thinking.
* Monitor shipped AI experiences for quality, failure modes, adoption, business impact, and operational risk.
* Collaborate with design to create intuitive AI UX, including graceful failure states, user control, transparency, and feedback mechanisms.
* Work with legal, security, compliance, and policy partners to support responsible deployment.
* Enable sales, support, customer success, and marketing with clear positioning, demos, launch materials, and customer narratives.

What you need to have:
* 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.
* Demonstrated ability to build, ship, prototype, or meaningfully contribute to technical products.
* Familiarity with modern AI tools and workflows, including hands-on use of AI assistants, coding agents, or product/research harnesses.
* Working knowledge of LLM product patterns: prompt design, context engineering, tool/function calling, agents, evaluation, failure modes, and when retrieval or external knowledge sources are useful.
* A strong evaluation mindset: you can define what "good" means, measure quality, find regressions, and connect AI performance to user and business outcomes.
* Technical fluency with APIs, data, product analytics, and system tradeoffs (SQL, Python, or lightweight scripting is helpful but not required).
* Ability to distinguish between a model problem, data problem, UX problem, workflow problem, and expectation-setting problem.
* Clear communication with both technical and non-technical audiences.
* High ownership and comfort working in ambiguity.

What makes you stand out:
* Experience shipping AI, ML, automation, data, developer, or workflow products.
* Experience creating and running evaluations for AI systems (test sets, grading rubrics, failure analysis, regression tracking, human review workflows).
* Experience with observability, quality dashboards, annotation workflows, or human-in-the-loop systems.
* Experience with enterprise AI, regulated industries, privacy-sensitive products, or compliance-heavy environments.
* Familiarity with retrieval systems, search, knowledge management, or other ways of giving AI systems useful context.
* Background in engineering, data science, research, technical consulting, design, or founder-like product work.

Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one "anchor day" per week on which their full team will be together in person.