Technical Product Lead, Voice AI Research Team

Job Description

Job Description

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!

 

We’re moving fast, and the numbers speak for themselves:

- Partnered with enterprise brands like Google, AAA, Ro, Coursera

- Raised $82M (top tier investors including Emergence & Homebrew)

- Completed 250M+ calls

- Driven $7B revenue for customers

- Scaled to $##M ARR

- Built amazing NYC (Midtown) in office culture

ABOUT THE ROLE:

As a Technical Product Lead on the Voice AI Agent team, you'll drive the experience that matters most: making Regal's voice AI agents indistinguishable from the best human agents and the highest-performing in the market.

You'll partner closely with engineering to set the product vision for how Regal evaluates, benchmarks, and continuously improves agent quality—building the eval frameworks, defining the performance bar, and translating frontier AI research into production gains our customers can feel on every call.

This role sits at the heart of what makes Regal win. You'll work across infrastructure and applied to drive decisions that directly impact conversation quality and competitive differentiation. If you want to shape what "best-in-class" means for Voice AI—and have the technical depth and product instinct to back it up—this role is for you.

RESPONSIBILITIES:

Define and Own the Quality Bar: Partner with engineering to establish Regal's point of view on what makes the best Voice AI agent—across naturalness, accuracy, task completion, and conversational flow. Translate that vision into measurable standards the entire organization rallies around.

Optimize the Latency-Cost-Intelligence Tradeoff: Develop the product strategy for balancing response time, inference cost, and model capability. Partner with engineering to architect a pipeline where customers get the smartest, fastest responses at sustainable unit economics.

Build Evaluation & Benchmarking Frameworks: Develop comprehensive eval sets, automated regression suites, and A/B testing infrastructure to ensure Regal's agents stay top-performing as models, prompts, and configurations evolve.

Stay at the Frontier: Track emerging trends in LLMs, speech-to-text, text-to-speech, and real-time inference. Evaluate new models, techniques, and architectures and translate the ones that matter into Regal's production stack.

Drive Competitive Differentiation: Develop and execute a strategy for how Regal's Voice AI agents outperform alternatives—whether through model selection, latency optimization, or proprietary fine-tuning.

Bridge Customers and Infrastructure: Go deep with customers to understand what "quality" means in their specific context (industry, use case, caller expectations), then translate those insights into infrastructure and model-level improvements that scale across the platform.

Measure, Iterate, Ship: Define success metrics for agent quality (e.g., conversation completion rate, caller sentiment, response latency percentiles, escalation rate). Build dashboards, run experiments, and drive a continuous improvement loop with engineering and applied AI.

Align and Communicate: Set a clear vision for the Voice AI team and communicate it crisply to leadership, engineering, and cross-functional stakeholders. Manage the roadmap, make hard prioritization calls, and keep the team moving fast toward outcomes that matter. ABOUT YOU:

Technical Depth with Product Instinct: 4–6 years of experience as a Product Manager, Product Engineer or founder, ideally working on AI/ML products, infrastructure, or developer platforms. This role is Product lead for a research team, so you're comfortable navigating model architectures, inference pipelines, and API design—and you know how to translate that understanding into product decisions that move metrics. 

Eval & Data Mindset: You think in experiments, benchmarks, and feedback loops. You've built or contributed to evaluation frameworks, A/B testing programs, or quality scoring systems—and you understand why rigorous measurement is the foundation of any AI product.

Natural Leader: You set a vision and bring others along. You communicate complex tradeoffs crisply, make decisions with incomplete information, and create clarity for your team in ambiguous, fast-moving environments.

Deeply Curious, High Agency: You don't wait to be told what to investigate. You dig into call recordings, run your own experiments, read research papers, and chase down the root cause. You act with urgency and ownership.

Preferred Background: Computer Science, Math, or Engineering background preferred but not required. What matters is that you can go deep on technical problems and come back with a clear product direction. Benefits/Perks

• We care about your health! 
• Medical, Dental, and Vision plans - 80% covered by the company
• Flexible PTO & 11 paid holidays/year 
• Subsidized Class Pass membership
• 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!

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.

POSITION LOCATION & OFFICE DETAILS:

 

This position is only available in New York City (HQ- Midtown). Hybrid roles are required in office T/W/TH and office optional M/F.

 

*If you think you’re missing relevant experience but you’re hungry and a fast learner (and can prove it), we want to hear from you!

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.