ABOUT US:

Founded in 2020, Regal is the AI Agent Platform. Regal gives every company the tools to transform customer communications with delightful AI Agents that are connected to your data, easy to customize and monitor, always-available, and ready to take action. Power better support, sales and operations – with way less effort. Our founders, Alex Levin and Rebecca Greene helped build Angi (Angie’s List, HomeAdvisor and Handy) to over $1.5B in revenue.

Based in Manhattan, we’re building an in-person culture of entrepreneurs who want to win and build something meaningful. We’re backed by top investors including Founder Collective, Homebrew and Emergence Capital.

Come join us as we create a category-defining company, and follow Regal's company page on LinkedIn to stay up-to-date on our journey and current job openings!

ABOUT THE ROLE:

We believe that ten years from now, 90% of businesses interactions with their customers will be handled by autonomous AI Agents. This role is at the forefront of defining those AI Agents that all of us will speak to.

The AI Agent Product Specialist role starts with two weeks of intensive training where you will learn to build AI Agents using the Regal AI Agent Platform. Get up to speed on our prompting best practices, function building, and the Regal Operating System. From then on, you’re writing the script. We view this role as a jumping off point for entry-level talent looking to start their careers in the exploding field of AI. After 1-2 years in this role, you will be prepared to take on more senior roles at Regal in engineering, product management or customer success.

AI Product Specialists at Regal own the creation and refinement of voice prompts, and conversation flows of AI Agents. You’ll blend prompt engineering techniques with user-focused product sense to deliver natural, brand-aligned interactions that meet business objectives. You’ll become an expert at the different settings/toggles/techniques that STT providers, TTS providers and LLMs expose to tune the performance of AI Agents. And with new use cases, you’ll pioneer new prompt engineering techniques, build new functions and deliver product feedback to the Regal product and engineering teams on new feature sets to enhance AI Agent performance. Finally, you’ll own Quality Control and testing of AI Agents to ensure they meet quality standards.

RESPONSIBILITIES:

Understand customer requirements: Work with AI Forward Deployed engineers to understand customer use cases, requirements for AI agents and their business objectives. Review customer’s existing human agent call recordings, scripts, training documents, FAQs/knowledge bases and brand guidelines to inform their AI Agent
Shape Conversational Experiences: Build AI Agents on the Regal AI Agent Platform leveraging prompt engineering and conversational flows; tune AI agent settings (STT, LLM, TTS) to achieve the conversational quality that is Regal’s signature and that meets customer’s requirements and business objectives.
Build Custom Functions/Tooling: Understand the limitations of LLMs and where code is needed to achieve certain use cases/performance. Use your coding chops to build custom functions that allow your AI Agents to take actions such as validate zip code, schedule callback, update profile
QA Test: Develop test cases and thoroughly test your AI Agents to ensure they pass Regal and the customer’s quality bar. Develop tooling, where needed, to scale QA testing and deliverables to build customers’ confidence in AI Agents so they don’t have to put QA hours against it
Iterate & Learn: Review agent performance in partnership with AI Forward Deployed Engineer who owns the client relationship. Iterate the AI Agent based on customer success criteria
Codify Best Practices: Leverage, share, and document best practices for building AI Agents and achieving certain use cases. Participate in prompt engineering forums and research best practices to add to our own techniques. Document what we’ve learned in a digestible way for internal and external consumption
Deliver Product Feedback: Work closely with Regal PMs and Engineers to give feedback on the Regal AI Agent Platform. As the primary user of the product, you’ll spot issues, product gaps, and new capabilities that will help you deliver better performing AI Agents faster – help inform these features!
Support Sales Demos: Work with the sales team to build AI Agent MVPs during the sales process to demo agent capabilities to prospects

ABOUT YOU:

Technical Chops: You’ve received a Bachelor’s or Master’s degree in a technical field (i.e. Computer Science, Engineering, Data Science) or have equivalent experience with prompt engineering
Professional Work Experience: You have 1-2 year(s) of work or internship experience at start-up tech companies, or impressive personal/school projects that you can provide documentation for
Demonstrated Curiosity for AI & Voice: You’re excited about the potential of Voice AI, and keep up with the latest products in the space. You’ve experimented with conversational design or prompt engineering for a school, work or personal project.
Analytical Thinking & Problem Solving: You see beyond the immediate ask, being able to break down problems into their component parts and tackle them iteratively. The ideal candidate likes to tinker and try new approaches, borrowing ideas from others and building from their own previous experiences
Time Management Skills: You know how to prioritize among competing tasks (or ask for help when needed), manage deadlines, and proactively keep your team & other stakeholders in the loop
Relentless Ownership: You own accountability for the success of your work, making smart trade-offs, iterating quickly, and doing whatever it takes to ship on time. “Not my problem” isn’t in your vocabulary
Entrepreneurial DNA: You’re considering being a founder one day. You thrive in fast-paced, ambiguous environments and absorb everything. Adaptability and growth mindset are qualities that help you navigate change and complexity with ease.

AI Product Specialist vs. AI Forward Deployed Engineer - What's the Difference?

The AI Product Specialist is more internal-facing, part of a centralized team using the Regal AI Agent Platform to build and test AI agents, codifying best practices and processes for AI Agent development and QA testing, and giving feedback to our product and engineering teams on how the platform needs to evolve (as well as building demos for the sales and marketing teams and working on internal projects). AI Product Specialists have a technical degree, but only 0-2 years of previous experience.
The AI Forward Deployed Engineer is more customer-facing, owning the launch and overall success of each AI Agent deployment and customer relationship, ensuring AI Agents can successfully integrate into the customer’s existing systems and workflows and achieve their business goals (as well as growing revenue by identifying more use cases and opportunities for AI Agents). AI Forward Deployed Engineers have 3+ years in a technical customer-facing role (e.g., Solutions Engineer, Implementation Consultant) or have PM experience in a tech environment

BENEFITS/PERKS:

We care about your health!
Medical, Dental, and Vision plans - 80% covered by the company
Flexible PTO & 11 paid holidays/year
We care about future you!
401k Plan
Paid parental leave
Pre-tax commuter benefits
We care about connection!
In-office breakfast and snacks daily
Happy hours, team outings, & annual off-sites
Complete laptop workstation
& more to come!

POSITION LOCATION & OFFICE DETAILS:
This position is only available in New York City (HQ- NoMad). Hybrid roles are required in office T/W/TH and encouraged 5x/week.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

The reasonably estimated base salary for this role is provided as a range within this job description. All offers include a competitive equity package and some offers may additionally include a variable compensation component. Actual compensation is determined on an individualized basis taking into consideration factors such as the candidate's skills, location, qualifications, experience, and relevant education or training. In addition, Regal offers a comprehensive set of employee benefits which are listed above. Details about the compensation package will be finalized at the time of offer.

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AI Product Specialist