招聘
ABOUT THE ROLE:
We're looking for a Director of Engineering, Agentic AI to lead Twelve Labs’ agentic platform and related developer experience (APIs, SDKs & tooling) that enables developers to build video-native agents—while also owning flagship end-user applications that validate and accelerate the platform. You will own the full journey from agent capabilities to production user applications. You'll build and lead multiple engineering teams, drive execution with speed and predictability, and shape the technical direction of our product stack. This is a role for a builder who leads from the front. You're deeply technical, close to the code on the things that matter, and energized by the challenge of shipping high-quality products in a fast-moving AI company. You pair strong people leadership with the judgment to make sound technical and product trade-offs under ambiguity.
IN THIS ROLE, YOU WILL
LEAD VIDEO AGENT PLATFORM DEVELOPMENT:
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Drive the development of Twelve Labs' video agent platform:
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Video ingestion & indexing that enables complex agentic workflows
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Agent orchestration runtime and core capabilities such as planning, tool use, multi-step reasoning
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Tooling for evaluation, observability, and debugging
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Reliability, latency, and cost-to-serve for agent workflows
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Safety/guardrails for agent actions
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Own the end-to-end delivery of flagship end-user applications — from concept through launch and iteration.
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Own the platform product surface: API design and SDKs
Own Delivery & Execution:
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Own delivery, quality, and operational excellence across your teams.
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Drive fast, predictable release cycles: planning, weekly reviews, and retrospectives that lead to improvements.
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Translate product and company goals into clear technical plans, milestones, and timelines. Make trade-offs explicit and manage dependencies across teams.
Build and Lead the Org:
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Build, lead, and grow your teams (through TLMs and Senior/Staff ICs).
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Hire exceptional talent and raise the bar continuously. Coach and develop leaders, manage performance decisively, and build clear growth paths for managers and ICs alike.
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Create a culture of ownership, speed, and craft — where teams ship with urgency but never sacrifice reliability or user experience.
Technical Excellence & Architecture:
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Stay hands-on where it matters most: architectural decisions, critical-path code reviews, and high-risk technical areas.
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Set and enforce a high quality bar across the stack: testing strategy, performance, reliability, observability, and CI/CD practices.
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Own production readiness: instrumentation, incident hygiene, latency, security and cost-to-serve.
Partner Across the Organization:
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Collaborate deeply with Product, Design, and Research to define product direction and ensure engineering execution matches the product vision.
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Work closely with modeling teams to translate model capabilities into reliable, production-grade product features.
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Represent engineering in leadership forums and contribute to company-wide technical strategy.
YOU MAY BE A GOOD FIT IF YOU HAVE:
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12+ years of professional software engineering experience
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7+ years of engineering leadership experience leading multiple teams (through Engineering Managers and Staff+ Individual Contributors).
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Experience building intelligent or agentic systems: agent platforms, tool-use frameworks, multi-step orchestration, or autonomous workflows on top of foundation models. You understand both the product surface and the underlying system complexity these require.
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Track record of shipping delightful, polished end-user experiences — you care deeply about what customers see, touch, and feel, and you hold a high bar for product quality, responsiveness, and craft.customer-facing
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Strong system design instincts with the ability to review architecture, challenge assumptions, and guide high-quality technical decisions
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Demonstrated experience building high-velocity engineering cultures: small batches, rapid iteration, tight feedback loops, and a bias toward getting working software in front of users quickly.
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Excellent people leadership: hiring world-class engineers, performance management, coaching, and growing future engineering leaders. You've built teams that ship fast and sustain quality.
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Strong communication skills with the ability to align cross-functional teams around priorities, trade-offs, and deadlines.
PREFERRED QUALIFICATIONS:
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Experience with video pipelines, video understanding, or multimodal systems.
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Background in building both developer platforms (APIs, SDKs, developer tools) and consumer-facing applications.
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Startup experience, especially in high-growth or early-stage environments.
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Prior experience partnering closely with applied ML or research teams to productionize model capabilities.
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关于Twelve Labs

Twelve Labs
Series ATwelve Labs is an AI company that develops video understanding technology using multimodal foundation models. The company provides APIs and tools for developers to build applications that can search, analyze, and generate insights from video content.
51-200
员工数
San Francisco
总部位置
评价
3.8
10条评价
工作生活平衡
4.2
薪酬
2.5
企业文化
4.0
职业发展
2.8
管理层
3.2
65%
推荐给朋友
优点
Good work-life balance
Supportive team and environment
Friendly coworkers and team spirit
缺点
Poor compensation/pay not competitive
Limited career advancement opportunities
Poor management and lack of direction
薪资范围
5个数据点
Senior/L5
Intern
Senior/L5 · Machine Learning Engineer
1份报告
$318,500
年薪总额
基本工资
$245,000
股票
-
奖金
-
$318,500
$318,500
新闻动态
Twelve Labs announced on the 1st that it has built an AI archive that allows users to quickly search.. - 매일경제
매일경제
News
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3w ago
Tried a bunch of “popular” AI tools for organizing recordings… some hot takes
I’ve been cleaning up a few months’ worth of recordings and video clips lately (meetings, random notes, saved content, etc.), so I figured I’d finally try some of the AI tools everyone keeps recommending. Still wanna pick one tool to be my go-to tbh. Just wanna say upfront, this is purely my personal experience. Not saying any of these are bad, just what worked / didn’t work for me.(no affiliate links, just sharing my feeling) - Otter.AI Probably the most well-known one. Transcription is solid
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4w ago
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How do you actually go back through meeting recordings without it taking forever?
Been in grad school long enough that lab meetings have become their own kind of stress. My PI throws out ideas mid-sentence, keeps going, and I'm nodding, then I'm back at my desk and realize I've retained maybe half of it. Started recording everything a while back. (of course, with everyone’s consent before recording) It helped, but reviewing became its own problem. I'd scrub through an hour of audio trying to find one 15-second comment. Been trying a few different AI tools for this over the
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4w ago
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Twelve Labs introduces video AI search on Gettyimagebank - 디지털투데이
디지털투데이
News
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4w ago