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Currently tracking 22 active AI roles, up 32% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $116k–$264k (avg $186k).

Hiring
22 / 26
Momentum (4w)
↑+18 +32%
74 opens last 4w · 56 prior 4w
Salary range · avg $186k
$116k–$264k
USD · disclosed roles only
Tracked since
Sep '25
last role yesterday
Hiring velocityscroll left for older weeks
1 new role
Sep 22
2 new roles
Oct 6
1 new role
13
3 new roles
20
3 new roles
Nov 10
4 new roles
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Dec 1
3 new roles
8
1 new role
15
1 new role
22
1 new role
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2 new roles
Jan 5
6 new roles
12
18 new roles
19
13 new roles
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6 new roles
Feb 2
8 new roles
9
8 new roles
16
10 new roles
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4 new roles
Mar 2
24 new roles
9
7 new roles
16
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15 new roles
30
12 new roles
Apr 6
14 new roles
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31 new roles
20
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26 new roles
May 4
6 new roles
11
Klaviyo

Klaviyo

Enterprise · Marketing automation

HQ
Massachusetts, US
Founded
2012
Website
klaviyo.com

Jobs (2)

22 AI · 238 total active
FilteredStageData×
Show
Active onlyAI only (≥ 7)
Stage
AllData · 2Serve · 3Agent · 33Ship · 4
Function
AllProduct · 143Engineering · 95
Country
AllUnited States · 187Ireland · 23United Kingdom · 15Australia · 6Singapore · 5Germany · 2
Sort
AI scoreRecentTitle
TitleStageFunctionLocationFirst seenAI score
Senior Software Engineer - Analytics Data Engineering
This role focuses on building and owning the data foundations that power Klaviyo's Analytics & AI engine. The Senior Software Engineer will design and implement scalable data pipelines and analytics models to transform large volumes of event data into actionable insights, enabling AI/ML products and customer-facing analytics features. The role involves collaborating with AI/ML teams, mentoring other engineers, and evolving technical standards for data engineering.
DataEngineeringBoston, MAJan 125
Engineering Manager - Data Automation
Engineering Manager for the Data Automation team at Klaviyo, focusing on building and scaling data infrastructure. The role involves leading a team of 7+ engineers, defining technical vision, and optimizing infrastructure. A key aspect is transforming workflows by integrating AI to build smarter systems and improve efficiency, though the core deliverable is data infrastructure rather than AI models themselves.
DataEngineeringBoston, MAJan 6
5