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Regal is an AI Agent Platform founded in 2020 that enables companies to transform customer communications with AI agents connected to their data. The company has raised $82M from top-tier investors (Emergence Capital, Homebrew, Founder Collective), partnered with enterprise brands like Google, AAA, Ro, and Coursera, and has completed 500M+ calls driving $7B in revenue for customers. Regal is based in Manhattan with an in-person entrepreneurial culture.
As Engineering Manager, you will lead and grow a team of 3–5 engineers while staying hands-on with Python and debugging production issues. You will own the observability and evaluation roadmap—tooling that surfaces how voice agents perform and frameworks that enable systematic quality evaluation. Key responsibilities include:
• Lead team growth, set expectations, support career development, and maintain high hiring standards
• Own execution of observability tooling that provides visibility into voice agent behavior in production
• Build evaluation frameworks allowing the organization to systematically improve voice agent quality
• Manage complex external and internal integrations that connect systems and scale with business growth
• Support the Copilot product roadmap (a customer-facing product for iterating on voice agents)
• Partner with product teams to translate voice-agent quality signals into actionable metrics
• Remove blockers through process adjustment, technical pairing, and cross-functional problem-solving
• Be actively involved in hiring: sourcing, interviewing, and onboarding
You will own observability tooling, evaluation frameworks, integrations infrastructure, and the Copilot customer-facing product.
REQUIREMENTS:
• 6+ years of experience in a relevant engineering role
• 1–3 years of experience managing a team
• Hands-on experience with Python and TypeScript; able to write and debug code at a senior level
• Solid experience with AWS (Lambda, SQS) and streaming systems (e.g., Kinesis)
• Comfortable managing ambiguity in a space still being defined (observability + evaluation for AI agents)
• Strong written and verbal communication skills; able to work with technical and non-technical stakeholders
• Track record of mentoring engineers and helping them grow
NICE TO HAVE:
• Experience with MCP (Model Context Protocol) or building agentic applications
• Background in observability, monitoring, or evaluation tooling
• Experience working adjacent to applied AI or ML teams
• Prior startup experience at Series B–D stage
