AI Systems Engineer

AppLovin • Palo Alto, CA

5d

About The Position

About AppLovin AppLovin makes technologies that help businesses of every size connect to their ideal customers. The company provides end-to-end software and AI solutions for businesses to reach, monetize and grow their global audiences. For more information about AppLovin, visit: www.applovin.com . 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. Fortune recognizes AppLovin as one of the Best Workplaces in the Bay Area, and the company has been a Certified Great Place to Work for the last four years (2021-2024). Check out the rest of our awards HERE . About the role We are building a layered AI intelligence system — a multi-layer agent architecture with a dynamic router, context engine, execution loop, verification layer, and eval feedback cycle — designed to handle long-horizon business tasks that cannot be accomplished in a single model inference. We are looking for engineers who understand that building with LLMs is not the same as building conventional software — and who find that difference interesting, not frustrating. You will own one or more layers of our AI system, from design through production, and iterate on them based on real-world failures. What you will own You will be matched to one of these layer areas based on your background and interest: Context engine: design and operate the RAG pipeline, memory architecture, MCP tool integrations, and prompt library that give the system company-specific knowledge at inference time Execution loop: build the action-observe-act cycle, tool integrations, state management, and logging infrastructure that let the system pursue multi-step goals Verification layer: design the checker model, confidence scoring, and human escalation logic that prevents the system from committing to bad outputs What we are looking for 1–3 years of experience building real systems that use LLMs — not just calling an API, but designing context, handling failures, and shipping to users Strong software engineering fundamentals: you write clean, testable code and you think about what happens when things break Genuine curiosity about how LLMs behave: you have noticed patterns in how models succeed and fail, and you have opinions about why Ability to move quickly and iterate: we are building in a new space and the path forward involves learning from production Nice to have Experience with vector databases, embedding models, or retrieval systems Familiarity with agentic frameworks: LangChain, LlamaIndex, AutoGen, or similar Experience designing prompts systematically — treating prompt design as an engineering discipline AppLovin provides a competitive total compensation package with a pay for performance rewards approach. Total compensation at AppLovin is based on a number of 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 (as applicable) may be provided as part of a total compensation package, in addition to dental, vision, and other benefits. Other Types of Pay: Equity eligible Health Insurance: Medical, Dental, Vision, Life, Disability Retirement Benefits: 401(k) Retirement Plan Paid Time Off: Unlimited Discretionary Time Off Paid Holidays: 10 paid holidays per year Paid Sick Leave: 80 hours per year 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 [email protected]. CA Base Pay Range $172,000 - $258,000 USD AppLovin has become aware of a scam targeting jobseekers with fake “app optimization” and similar roles. We do not ask our candidates to download apps or make any form of payment(s). AppLovin works with applicants through our Careers page and applovin.com email addresses. If you are contacted through other unofficial channels (such as WhatsApp or Telegram) or asked to download an app or make a payment, these contacts are not legitimate. Confirm the information here and contact us directly with any questions. AppLovin is proud to be an equal opportunity employer that is committed to inclusion and diversity. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status, or other legally protected characteristics. Learn more about EEO rights as an applicant here . 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 [email protected]. AppLovin will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in California, learn more here . To support an efficient and fair hiring process, we may use technology-assisted tools, including artificial intelligence (AI), to help identify and evaluate candidates. All hiring decisions are ultimately made by human reviewers. Please read our Global Applicant Privacy Notice to learn more about how AppLovin processes your personal information.

Requirements

• 1–3 years of experience building real systems that use LLMs — not just calling an API, but designing context, handling failures, and shipping to users
• Strong software engineering fundamentals: you write clean, testable code and you think about what happens when things break
• Genuine curiosity about how LLMs behave: you have noticed patterns in how models succeed and fail, and you have opinions about why
• Ability to move quickly and iterate: we are building in a new space and the path forward involves learning from production

Nice To Haves

• Experience with vector databases, embedding models, or retrieval systems
• Familiarity with agentic frameworks: LangChain, LlamaIndex, AutoGen, or similar
• Experience designing prompts systematically — treating prompt design as an engineering discipline

Benefits

• Equity eligible
• Health Insurance: Medical, Dental, Vision, Life, Disability
• Retirement Benefits: 401(k) Retirement Plan
• Paid Time Off: Unlimited Discretionary Time Off
• Paid Holidays: 10 paid holidays per year
• Paid Sick Leave: 80 hours per year

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed
• Number of Employees: 501-1,000 employees