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Open nowPosted 7 days ago

Engineering Manager, Voice AI

Calliere58 open roles

Pay
$220,000 – $280,000 a year
Where
Remote
Work mode
Remote
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Your applicationOpen nowEngineering Manager, Voice AICalliere · Remote
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14.0% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
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  2. 4.7%3 days
  3. 14.0%7 days
  4. 22.5%14 days
  5. 38.3%30 days
  6. 59.0%60 days
This job: posted 7 days ago

The posting

Series B AI company | Full-time | 100% remote (US or Canada) Right now, somebody is calling their insurance company, their pharmacy, or their airline. There's a decent chance the voice that picks up, understands what they need, and actually fixes it was built by this team. No hold music. No "press 3 for billing." Just a problem solved. They're looking for an Engineering Manager to lead one of the squads making that happen. The snapshot Base salary US: $220,000 to $280,000 USD. Canada: C$190,000 to C$250,000. Set by level (Engineering Manager or Senior Engineering Manager). No variable or commission. Equity Meaningful stock options. Ownership is a real part of the pay philosophy here, not a footnote. Experience 10+ years in software engineering, 5+ of them managing engineers Team A squad of 8 to 15 engineers Location 100% remote, anywhere in the US or Canada Travel Meet up in person roughly every six weeks Work authorization Must already be authorized to work in the US or Canada. No sponsorship. Why this one is worth a look The problem is enormous. Customer service is close to a trillion-dollar problem and barely 1% of it is automated. There is a lot of road ahead. They picked the hard channel on purpose. Voice is the first thing people reach for and the toughest thing to automate well. That's where they started. This isn't a demo. They've had AI agents running in production for Fortune 500 enterprises since well before the generative AI wave, handling millions of calls a month across insurance, healthcare, retail, financial services and travel. The customers like it. Hundreds of enterprise deployments, and satisfaction scores most SaaS companies would envy. Small team, big leverage. A lean, senior group doing the work of a much larger one. Every engineer owns several initiatives. The role This is a people-leadership job, not a coding job. You won't be writing the code. You'll be building the team that does, and making strong senior engineers even more effective. You'll also sit as a peer on a tight management group that owns every engineering department decision together. What you'll actually do Lead and grow a squad of 8 to 15 engineers. Hiring, career growth, performance, budget and headcount are all yours. Sit at the table with the other engineering managers, who meet several times a week and make the department's calls as a group. Set the pace. Push back on the status quo. Build a team that digs in, ships fast and learns from what breaks instead of debating it to death. Deliver the work customers care about most, predictably and well, and stand behind your team's dates and results. Make your team genuinely AI-native. Take the scattered individual experiments and turn them into real team-level gains in speed, quality and time from idea to production. Work closely with Product, Delivery and other teams so the squad stays locked on real customer value, and close the loop after things ship. Requirements Who thrives here 10+ years in software engineering, with at least 5 managing engineers You've led teams of 8 or more and you've done the hard parts: hiring, growing people, and making tough performance calls Real early-stage or high-growth startup experience. You know what moving fast actually feels like. A servant-leadership style, and you're comfortable leading people you mostly see on a screen Bonus points: you've founded something, you're hands-on with AI tools, or you've worked around conversational AI, voice or telephony Under the hood The platform is a full stack of hard problems: Telephony and real-time voice Speech recognition and voice models LLMs with orchestration and failover across multiple providers A reasoning runtime that drives every conversation from start to finish Bot-building and conversation-design tools ML infrastructure and evaluation Production analytics on how every bot is performing Languages: Python, JavaScript, and a strongly typed functional language at the core. How they work They've reinvented their product, sales motion and deployment model, and they're leaning hard into a fail-fast, entrepreneurial culture. Try things, get it wrong quickly, learn, move on. Three ideas guide the team: Own it. Take responsibility, use every tool you've got to hit the goal, and give feedback openly and often. No ego. Humble and egalitarian. No task is too big or too small for anyone. Look at your own work with honest eyes. Step back, be critical of yourself, and trust your colleagues to point out your blind spots.

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