Forward Deployed Product Manager

present of AI; United States; On-site; USD 90,000 - 130,000; Full time

Job summary

present of AI is seeking a mid‑level professional to bridge customer success, product, and hands‑on AI work. You will own growing customer accounts, get each live with an engineer partner, and continually improve outcomes using logs, usage data and API docs. Emphasis on trust, teaching teams, and choosing problems that matter.

You will gain hands‑on AI experience deploying a live support agent in regulated settings, with daily use of AI coding tools and a path to broader impact across customers.

Qualifications

• This role requires at least 2 years accountable for customer outcomes.
• Ability to analyze logs and usage data to drive decisions.
• Familiarity with API documentation and integration basics.
• Experience building with AI in customer-facing contexts.

Responsibilities

• Own customer outcomes end to end across accounts.
• Work with engineers to deploy an AI agent for live use.
• Teach customers to self-serve and reduce support needs.
• Analyze usage data to inform product roadmap.

Skills

Customer outcomes

Logs analysis

Usage data

API docs

AI tooling

Tools

AI coding tools

Job description

This role sits between customer success, product and hands-on building. The person owns a set of growing customer accounts, gets each one live with an engineer partner, then keeps improving results and finding new uses. A strong candidate has at least two years of being accountable for customer outcomes, has earned trust with senior people at customers, and is comfortable digging into logs, usage data and API docs on their own.

How it fits the AI era

The day-to-day work leans on AI tools to investigate problems, test changes and ship fixes without waiting on engineers for every step. The product itself is an AI agent handling support in settings where mistakes are costly, so judgment about when a human should step in matters a great deal. What stays human is building trust with customer leaders, teaching their teams, and deciding which problems are worth solving for everyone.

How it builds AI experience

Someone in this seat would get repeated practice configuring, testing and deploying a live AI support agent for real businesses, including voice and identity checks in finance and health settings. The company also expects daily use of AI coding tools. To build similar experience beforehand, try a small project that automates a support workflow, and keep notes on what worked, what broke and how results were measured.

Worth showing

• Owning customer outcomes end to end
• Building with AI, with honest lessons
• Analyzing logs and usage data
• Teaching customers to self-serve
• Turning customer evidence into roadmap

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Lorikeet

AI customer-support agents built for the regulated industries where a wrong answer actually matters.