Director of Engineering

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, Home Advisor, 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 Linked In 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 500M+ calls
• Driven $7B revenue for customers
• Scaled to $##M ARR
• Built amazing NYC (Midtown) in office culture

We're hiring a Director of Engineering to own two of our most technically challenging areas: the real‑time systems that power every live call, and the applied AI research that determines how those calls sound and feel.

You'll lead two teams: one responsible for the real‑time call delivery infrastructure that handles every live voice interaction at scale, and one doing proprietary model work on the problems that matter most to voice quality, end‑of‑utterance detection, voice activity detection, answering machine detection, and STT accuracy. These are active, production‑impacting problems, not research projects.

This is the right role for someone comfortable at the intersection of applied AI and real‑time systems, not a pure researcher, and not a pure product EM. You’ll work closely with Regal's Staff+ AI Engineering lead as a peer and collaborator, and you'll have room to grow into broader engineering ownership as the team scales.

• Lead and develop engineers across two teams, set expectations, support career growth, and run a tight hiring bar. You thrive on managing people and view it as a privilege.
• Own the technical roadmap for real‑time call delivery and applied voice AI, in collaboration with Product, AI Engineering, and the broader engineering leadership team.
• Drive the applied AI roadmap: improving how AI agents talk to humans (pace, timing, accuracy, and warmth) and the contact center AI capabilities that make agents more effective in production.
• Do whatever it takes to unblock your teams, whether that's changing a process, pair debugging, or cutting through cross‑functional friction.
• Work closely with product and engineering leadership to drive innovation and collaboration.
• Maintain a strong peer relationship with Regal's AI Engineering lead, collaborative, not territorial. Applied model work intersects with research; managing that handoff well is part of the job.
• Represent engineering in cross‑functional conversations on voice quality, latency, and AI agent reliability.
• Be actively involved in hiring: sourcing, interviewing, and onboarding.

• Real‑time call delivery:
  The systems that route, handle, and manage live voice calls. Telephony reliability, call delivery s team is the layer where every agent capability meets every customer.
• Applied voice AI:
  Proprietary model work on the hardest voice quality problems: end‑of‑utterance detection, voice activity detection, answering machine detection, STT accuracy, and p95 latency. Small team, high‑leverage output.

• 8+ years of experience in software engineering, with meaningful time in systems where latency and reliability are first‑class constraints.
• 4+ years in engineering management, including experience managing mid to senior level engineers.
• An entrepreneurial mindset; we're not looking for someone to run a playbook. We want you to help build it.
• Comfortable operating at the boundary of research and engineering, you know how to take a model improvement and turn it into a production system,…