Product Designer

Meta•San Francisco, CA

10d•$201,000 - $278,000

About The Position

Meta is seeking a Product Designer to help build Meta Business Agent, a multimodal AI agent designed to answer customer questions, close sales, book appointments, and provide customer support around the clock. The role spans business-facing and customer-facing experiences across chat, voice, and visual surfaces, serving businesses from small businesses to enterprises. The designer will contribute end to end, from prototyping and interaction design to prompt and model behavior design, evaluation, and strategic product decisions with product and executive partners. The role combines product, interaction, visual, and model design. It involves writing and revising prompts, testing agent experiences, translating findings into prompt fixes or training signals, and defining evaluation approaches that measure agent quality. The designer will partner with engineering, data science, research, and other cross-functional teams to establish quality standards, build scalable systems, and shape multi-modal agent communication and product direction. The listed salary range is $201,000 to $278,000 per year, plus bonus, equity, and benefits.

Requirements

Bachelor’s degree in HCI, design, or a related field, or work experience designing and building agentic experiences.
11+ years designing software products focused on user experience, interaction design, and visual design that meet business objectives.
Experience building and maintaining evaluation pipelines for LLM products, including graders, rubrics, comparison sets, regression suites, and the infrastructure to run them across models.
Experience designing and building agentic experiences.
B2C or B2B experience.
Deep expertise in prototyping tools and ability to evaluate and advance design craft across fidelity levels.

Nice To Haves

Experience implementing responsible and ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.
Experience translating product rubrics into training signals, including graders, human-feedback questions, or preference pairs.
Experience shaping agent behavior on voice or other multimodal surfaces.
Ongoing AI skill development, such as prompt and context engineering or agent orchestration, and staying current with emerging AI technologies.
AI-native design fluency, including model design, generative AI logic, and defining assistant behavior and tone at the systems layer.
Front-end or notebook-to-app experience, and opinions about making evaluation results legible at a glance.
Experience with both B2C and B2B experiences.

Responsibilities

Write and revise prompts for Meta’s agentic tools, features, and product-surface behaviors; test experiences, address findings, ship prompt fixes, and verify the intended prompt is delivered.
Package issues that prompting cannot fix for training, including graders for clear behaviors and human-feedback questions and good/bad pairs for less-defined qualities such as writing quality.
Partner with engineering and data science to define quality expectations for agent output across chat, voice, and visual surfaces, and drive evaluation strategy.
Extend evaluation coverage beyond text to voice and visual agent output, defining how quality is assessed on conversational and visual surfaces.
Define quality bars that work across a broad range of businesses, from small businesses to enterprises, without bespoke rework.
Rapidly prototype ideas and experiences to bring concepts to life and help prioritize workstreams based on impact and feasibility.
Define, evolve, and unify visual and interaction systems that scale across products and platforms.
Define evaluation strategy and build evaluations, golden sets, and judges independently and with data science and engineering partners.
Use familiarity with software code and internal tools to update language and prompts, review changes, verify shipped experiences, and build logic that adapts agent behavior to context.
Work with product and cross-functional partners to define a strategy for multimodal agent communication.
Present design strategy and rationale to leadership and cross-functional executives, building organizational alignment on product direction and influencing priorities across product, engineering, research, and content strategy.