Full-Time

AI Agent Product Manager

Applied Labs

Applied Labs

11-50 employees

Platform for building customer-support AI agents

Compensation Overview

$150k - $200k/yr

+ Equity package

New York, NY, USA

In Person

Bachelor's

Category
Product (1)
Required Skills
LLM
Product Management
Machine Learning

Get referred to Applied Labs

See people who can refer or advise you

Requirements
  • At least 2 years of experience in product, engineering, and/or consulting.
  • Excellent cross-functional and customer communication skills.
  • A technical degree in computer science, engineering, or a related field.
  • Strong ownership and the ability to prioritize impactful work for customers.
  • Ability to move quickly, handle ambiguous problems, bias toward decisive action, and drive clear outcomes and key performance indicators.
Responsibilities
  • Build AI products from 0 to 1 by working directly with engineers and customers to define, build, and launch AI-powered products.
  • Partner with customers to understand their workflows, challenges, and needs; translate these into requirements and solutions; demonstrate products; gather feedback; and ensure the team addresses customer needs.
  • Own the roadmap for core AI products, balance technical tradeoffs with customer value, prioritize work, define success metrics, and ensure the team ships with quality and speed.
  • Communicate complex technical concepts to engineers and non-technical stakeholders to ensure alignment from leadership to frontline users.
  • Handle edge cases, write product requirements documents, test features, and work through ambiguity to deliver outcomes.
Desired Qualifications
  • Experience at an early-stage, high-growth startup.
  • Background in artificial intelligence or machine learning products or developer platforms.

Applied Labs provides a platform to build and manage AI agents that automate complex support and back-office tasks across channels like chat, email, and phone. These agents can perform actions in backend systems (for example refunds and CRM data syncing) to enable omnichannel customer interactions and workflow automation. The platform emphasizes a human-in-the-loop approach with guardrails, monitoring, escalations, and built-in auditing and testing tools to ensure reliability. Its goal is to help enterprises implement AI-driven back-office and customer-support workflows across industries such as finance, legal, logistics, insurance, and healthcare.

Company Size

11-50

Company Stage

Seed

Total Funding

$4.2M

Headquarters

New York City, New York

Founded

2024

Get referred to Applied Labs

See people who can refer or advise you

Simplify Jobs

Simplify's Take

What believers are saying

  • July 28, 2026 site claims 90%+ CSAT and zero-downtime migration.
  • June 2026 blog says Applied Assistant learns company tone, policies, and customers.
  • July 10, 2026 partnerships page targets consultancies and integrators, widening distribution.

What critics are saying

  • Two reviews on G2 by August 3, 2026 are too few for durable product validation.
  • Applied Labs still shows seed-stage hiring and three open roles, signaling thin execution capacity.
  • Intercom, Zendesk, and Sierra can outspend it, commoditizing AI support by 2027.

What makes Applied Labs unique

  • May 13, 2026, Applied Labs launched a self-serve AI CX platform.
  • Its stack combines builder, unlimited-seat help desk, AI-native CRM, and Alfred assistant.
  • Human-in-the-loop guardrails and evaluation tools target high-stakes support workflows.

Help us improve and share your feedback! Did you find this helpful?

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Unlimited Paid Time Off

Relocation Assistance

Company Equity

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

20%

2 year growth

0%
Business Insider
Jan 28th, 2025
Applied Labs raises $4.2M to make it easy to build high quality AI support and ops digital employees

New York, Jan. 27, 2025 (GLOBE NEWSWIRE) -- Every company today faces mounting pressure to deploy AI, but most solutions fall short on reliabili...