Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 7
API @ 4
AWS @ 4
Agentic Systems @ 4
Audit
Azure @ 4
Communication @ 7
Data Pipelines
Data Science @ 6
GCP @ 4
Git @ 4
GitHub @ 4
LLM @ 3
Mathematics @ 6
Python @ 7
SQL @ 7
Security @ 3
Statistics @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
About the Role
Join AppLovin's AI Strategy team to drive the adoption of AI and automation across business teams. This role sits at the intersection of business operations, data, engineering, and AI, helping teams turn manual workflows into scalable, secure, and measurable AI-enabled processes.
Success in this role means enabling teams across the organization to use AI safely and with increasing independence, replacing manual processes with repeatable workflows, scaling high-impact use cases across functions, and delivering measurable improvements in productivity, quality, reliability, and operational risk.
Responsibilities
- Define and execute AI adoption roadmaps across business functions.
- Partner with Finance, Legal, HR, and other teams to identify high-value opportunities for AI, automation, and workflow improvement.
- Build monitoring and alerting for AI-powered data pipelines, integrations, and automations.
- Establish documentation for dashboards, metrics, data sources, ownership, and calculation logic.
- Operate an internal AI skills and automation program, including user onboarding and enablement, contributor and skill-author approvals, security and governance reviews, and adoption, usage, and quality tracking.
- Build, launch, and manage team-specific libraries of reusable AI skills, tools, and workflows.
- Develop and support internal AI champions and power users across the organization.
- Coordinate secure integrations between AI tools and enterprise systems, data platforms, APIs, spreadsheets, and third-party services.
- Partner with IT, Security, Engineering, Data, and business teams to establish cloud, source-control, identity, permissions, and service-account infrastructure.
- Develop reusable automation patterns for moving data between Python-based workflows, APIs, databases, spreadsheets, and internal systems.
- Translate operational business processes into reusable AI capabilities, including multi-source data reconciliation, query and scripting assistance, data-import troubleshooting, integration diagnostics, audit and evidence collection, user-access and permissions reviews, reporting, and operational workflow automation.
- Interview business users to assess AI maturity, identify high-value use cases, surface capability gaps, and develop internal champions.
- Create practical data-classification and governance guidance for safe AI use.
- Define and track success metrics across adoption, quality, time savings, reliability, operational efficiency, and risk reduction.
- Build a repeatable onboarding framework and establish standards and reusable patterns that allow new teams to adopt AI safely and efficiently and successful workflows to scale across teams.
Requirements
- 3–6 years of relevant experience in business operations, strategy, data, automation, engineering, AI, consulting, or a related technical or operational role.
- Experience independently owning or driving cross-functional technology, automation, data, or AI initiatives from problem definition through implementation and adoption.
- Strong understanding of business operations and the ability to translate ambiguous operational problems into practical technical solutions.
- Experience with APIs, databases, cloud infrastructure, identity systems, Git-based workflows, and automation platforms.
- Strong working knowledge of Python and SQL.
- Familiarity with major LLM-based tools and platforms. Experience building AI workflows, agentic systems, reusable skills, automation loops, or autonomous workflows is strongly preferred.
- Experience integrating enterprise systems, data platforms, spreadsheets, APIs, and third-party services.
- Ability to establish lightweight governance and security controls without unnecessarily slowing adoption.
- Strong communication skills and the ability to work effectively with senior stakeholders and technical and non-technical teams.
- A practical, ownership-oriented mindset focused on deploying solutions that are scalable, reliable, measurable, secure, and reusable.
Preferred Education and Qualifications
- Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, Business Analytics, Economics, Mathematics, Statistics, or another quantitative or technically oriented field. Equivalent practical experience may be considered.
- Experience in business operations, consulting, strategy and operations, analytics, technical program management, automation, or internal tooling.
- Demonstrated experience deploying AI, automation, or data solutions into real business workflows.
- Experience with cloud platforms such as GCP, AWS, or Azure; source control such as Git or GitHub; and enterprise identity or access-management systems.
- Familiarity with AI governance, data classification, security reviews, access controls, monitoring, or workflow and model evaluation.
- Experience independently identifying high-impact opportunities, designing solutions, and driving adoption across multiple teams.
- Experience working in a fast-paced technology company or similarly high-ownership environment is a plus.
Compensation and Benefits
AppLovin provides a competitive total compensation package with a pay-for-performance rewards approach. Total compensation is based on factors including market location and may vary depending on job-related knowledge, skills, and experience. Depending on the position offered, equity and other forms of incentive compensation may be provided in addition to dental, vision, and other benefits.
Canada base pay range: $150,000–$200,000 CAD.
AppLovin is an equal opportunity employer committed to inclusion and diversity. Reasonable accommodations are available during the application or recruiting process. AppLovin may use technology-assisted tools, including artificial intelligence, to help identify and evaluate candidates, but all hiring decisions are ultimately made by human reviewers.