AppLovin

AppLovin

Partner Solutions Engineer

Palo Alto, CA · Mid

Sponsorship not specified$126k-$188kDetected 3 days ago
JavaScriptPythonSQLData AnalysisPerformance MarketingShopifyLeadershipCommunicationProblem SolvingPublic Speaking

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odds of building a lasting career here

55Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role82
Entry-level history0
PERM / green-card track0
Lottery odds (Level III)83
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~45% per draw at Level III). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Green-card filing pattern in this occupation

Context, not a finding about this posting: of this employer's 7 green-card filings in this occupation, 100% were for a worker who already held the job.

Green-card intent detected

AppLovin Corporation obtained a prevailing wage determination for Data Scientists in Palo Alto, CALIFORNIA on 2026-06-17. No matching green-card filing appears in our data yet. The determination expires in 9 days (2026-09-14), and a green-card filing must follow before then or the employer starts over.

Files H-1B transfers

7 transfer filings in the last year, covering 7 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • This role exists to make those integrations succeed, accelerate adoption of our CAPI and tracking infrastructure, and ensure that integration friction gets fed back into the product rather than buried in a ticket queue.
  • You will work directly with AppLovin's engineering teams and leadership, with real influence over how our integration ecosystem evolves.
  • Investigate, reproduce, and resolve technical issues with web SDK, CAPI, and API integrations, pinpointing root causes through data analysis

Responsibilities

  • This is not a traditional support role.
  • The remaining 10% is hands-on: when you see a recurring friction point, you build the fix.
  • The partners you support will be some of the most strategically important to Axon's growth.
  • Own the end-to-end technical onboarding and integration experience for strategic 3P partners across CAPI, web SDK, and APIs
  • Build internal tooling and scripts to streamline troubleshooting, automate validation steps, and accelerate partner debugging
  • Support new integration pilots across partners, owning sandbox validation and proactive issue resolution so core engineering stays focused on building
  • Drive adoption by translating complex technical requirements into clear, actionable guidance for both technical and non-technical audiences
  • To support an efficient and fair hiring process, we may use technology-assisted tools, including artificial intelligence (AI), to help identify and evaluate candidates.

Requirements

  • 2+ years of professional software engineering experience, with production-quality code in dynamic environments
  • Bachelor's degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience
  • Strong foundation in web-based integrations: experience with CAPI, server-side tracking, APIs, pixels, or equivalent ad tech infrastructure
  • Proficiency in at least one scripting or general-purpose language (Python, JavaScript, or similar) with the ability to build lightweight tooling independently
  • Experience querying large data sets with SQL

Nice to have

  • Experience in ad tech, performance marketing, or e-commerce advertising, with familiarity with attribution, data signals, ROAS, and measurement concepts
  • Hands-on experience with e-commerce platforms such as Shopify, Google Tag Manager, or equivalent
  • Track record of identifying product gaps from operational experience and driving improvements back into engineering roadmaps
  • Comfort operating in a fast-moving, ambiguous environment where the answer isn't always written down
  • AppLovin provides a competitive total compensation package with a pay for performance rewards approach.
  • Method of Application: Apply online
  • Application Window: The application window is expected to close within 30 days of the posting date.
  • All questions or concerns about this posting should be directed to peopleops@applovin.com.

Skills

  • About AppLovin
  • The company provides end-to-end advertising solutions for businesses to reach, monetize and grow their global audiences.

Compensation

  • 10 paid holidays per year
  • Paid Holidays: 10 paid holidays per year
  • CA Base Pay Range
  • $126,000 - $188,000 USD
  • 80 hours per year

Benefits

  • Unlimited Discretionary Time Off
  • 401(k) Retirement Plan
  • Paid Sick Leave: 80 hours per year
  • Paid Time Off:

Company info

  • About AppLovin AppLovin makes technologies that help businesses of every size connect to their ideal customers.
  • We are looking for a highly-motivated Partner Solutions Engineer - Ads in Palo Alto.
  • We are actively building next-generation integration flows with partners.
  • To deliver on this mission, our global team is composed of team members with life experiences, backgrounds, and perspectives that mirror our developers and customers around the world.
  • At AppLovin, we are intentional about the team and culture we are building, seeking candidates who are outstanding in their own right and also demonstrate their support of others.

Equal opportunity

  • equal opportunity employer that is committed to inclusion and diversity.
  • If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send us a request at jobs@applovin.com
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This listing is sourced directly from AppLovin's careers page and normalized into a canonical job model.