Software Engineer, Agentic AI and LLMs, Google Ads
- linkCopy link
- emailEmail a friend
Minimum qualifications:
- Bachelor’s degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages (e.g., Java, Python, Go, or C++), or 1 year of experience with an advanced degree.
- 1 year of experience with one or more of the following: Speech/audio systems, reinforcement learning (sequential decision making), ML infrastructure, or a distinct specialization in another machine learning field.
- 1 year of experience with end-to-end Machine Learning (including model deployment, model evaluation, data processing, and debugging).
Preferred qualifications:
- Master's degree or PhD in Computer Science, Computer Engineering, Machine Learning, or related technical fields.
- 2 years of experience with data structures or algorithms in either an academic or industry setting.
- 1 year of experience with LLMs, prompt design/optimization (e.g. APO), or modern agentic orchestration frameworks.
- Experience developing accessible technologies that comply with global usability and accessibility standards.
- Experience with full-stack development across back-end services, database schemas, APIs, and front-end frameworks (e.g., Dart, JavaScript, or TypeScript).
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
Google Ads powers digital commerce for millions of global businesses. Within Google Ads, the team is creating the next wave of intelligent, autonomous systems. Rather than relying on static interactions, the team builds conversational and agentic workflows that resolve complex advertiser inquiries across chat, email, and virtual meetings. We bridge frontier foundation models with massive-scale distributed infrastructure to build reliable, helpful, and safe enterprise assistants.
Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.
Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Write product or system development code using Java, Python, Go, or C++ to build and optimize high-throughput backend services, storage schemas, APIs, and data pipelines for massive-scale GenAI systems.
- Collaborate with peers and stakeholders through technical design and code reviews to ensure best practices amongst available technologies, focusing on style guidelines, checking code in, accuracy, testability, and efficiency.
- Contribute to existing technical documentation or educational developer content and adapt engineering specs based on system/program updates, prompt engineering variations, and internal and external user feedback loops.
- Triage issues and debug/track/resolve production anomalies by analyzing the sources of issues and their impact on hardware, network, or service operations, system latency, and output quality.
- Implement solutions in specialized ML areas utilizing ML infrastructure to contribute to model optimization, data processing, and Tier 2 on-call reliability.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy.
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.