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Google will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa.Minimum qualifications: Bachelor's degree in a technical field, or equivalent practical experience. 5 years of experience in program management. 2 years of experience developing or launching products or technologies within safety, security, privacy, or a related area. Experience with generative AI and machine learning Experience managing multi-quarter technical programs involving distributed systems, machine learning pipelines, or infrastructure. Experience designing cross-functional engagement models and operations to lead teams through the full execution lifecycle. Preferred qualifications: Master's degree. 7 years of experience in program or project management. Experience in content safety, Trust and Safety, responsible AI, or product policy, including evaluating malicious threats at scale. Experience driving alignment across a distributed landscape of stakeholders (e.g., central engineering, Trust and Safety, and various product teams) to land high-impact cross-functional efforts. Experience driving and critiquing technical requirements for sensitive, scalable detection systems, including Machine Learning (ML) and Large Language Model (LLM) concepts (e.g., transformers, activations, and efficient training, deployment). Understanding of adversarial dynamics, and prioritizing coverage gaps with a problem-centric mindset. About the jobA problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers. The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.Responsibilities Lead complex, multi-quarter initiatives to expand our content safety infrastructure. Manage ambiguous issues, such as integrating specialized safety classifiers or building rapid response capabilities for AI abuse vectors. Partner with cross-functional leaders to convert emerging threat intelligence and safety objectives into scalable, production-ready models and technical protections within our serving stack. Orchestrate the strategy and execution of our Safety Engineering teams. Ensure our programs tangibly reduce abuse prevalence, improve user safety metrics, and optimize the person hours required for model training and deployment. Manage global workflows, coordinating with regional teams to ensure continuous coverage, seamless handoffs, and timely integration and evaluation of safety models for business-critical Gemini releases. Coordinate between Infrastructure teams, generative AI product groups, and foundational model researchers to integrate safety signals into primary models. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google welcomes people with disabilities.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Taipei, Taiwan; Hong Kong.Minimum qualifications: Bachelor’s degree in a Science, Technology, Engineering, Mathematics, or related field, or equivalent practical experience. 3 years of experience in providing production-grade AI solutions to external or internal customers with L400-level in Python, and architecting AI systems on cloud platforms. Experience in developing generative AI (GenAI) solutions with foundation models, first-party model tuning, and advanced retrieval-augmented generation (RAG) architectures. Preferred qualifications: Master’s degree or PhD in Artificial Intelligence, Computer Science, or a related technical field. Experience in implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s ADK) and patterns like ReAct, self-reflection, and hierarchical delegation. Knowledge of large language model (LLM)-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing. Ability to implement agentic workflows incorporating MCP, tool-calling, and OAuth-based authentication. Ability to build full-stack applications that interact with enterprise IT infrastructures, and perform interviews to find the business problem and translate hardware/AI constraints for technical teams. About the jobThe Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners. In this role, you will be an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. You will manage blocker to production including solving the integration complexities, data readiness issues, and state-management tests that prevent AI from reaching enterprise-grade maturity. You will provide deployment of AI systems and act as a feedback loop, transforming field insights into Google Cloud’s future product roadmap.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Serve as the lead developer for AI applications, transitioning from prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive return on investment. Architect and code the connections between Google’s AI products and customers' live infrastructure, including APIs, legacy data silos, and security perimeters. Build evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency. Identify repeatable field patterns and technical friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the engineering teams. Co-build with customer engineering teams to instill Google-grade development best practices, ensuring project success and end-user adoption. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa.Minimum qualifications: Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience. 3 years of experience building and shipping production-grade AI-driven solutions to external or internal customers using Python, Typescript, or similar languages. Experience leading technical discovery sessions with business stakeholders and engineering teams to define AI and hardware infrastructure requirements. Experience building pipelines for structured, unstructured data, incorporating vector databases and RAG-like architectures to power enterprise-grade AI solutions. Experience architecting AI systems on cloud platforms (e.g., Google Cloud Platform (GCP)). Preferred qualifications: Master’s degree or PhD in AI, Computer Science, or a related technical field. Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s ADK) and complex patterns like ReAct, self-reflection, and hierarchical delegation. Knowledge of LLM-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing. About the jobAs a GenAI Forward Deployed Engineer (FDE) at Google Cloud, you are an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. Unlike traditional advisory roles, you function as an 'innovator-builder', moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment.In this role, you will manage blockers to production including solving the integration complexities, data readiness issues, and state-management challenges that prevent AI from reaching enterprise-grade maturity. By embedding with strategic accounts, you serve a dual purpose: providing "white glove" deployment of complex AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product road map.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, Model Context Protocol (MCP) servers) that drive Return on Investment (ROI). Architect and code the "connective tissue" between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters as part of an expert team. Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet the requirements for accuracy, safety and latency. Identify repeatable field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams. Co-build with customer engineering teams to instill Google-grade development best practices, ensuring project success and end-user adoption. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google welcomes people with disabilities.Minimum qualifications: Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience. 1 year of experience building and shipping production-grade AI-driven solutions to external or internal customers using Python, Typescript or comparable languages. Experience in applied AI, with a focus on building systems around pretrained models (e.g., prompt engineering, fine-tuning, Retrieval-Augmented Generation (RAG), orchestrating model interactions with external tools to deliver solutions). Experience architecting, deploying, or managing solutions on a cloud platform (e.g., Google Cloud Platform). Ability to communicate in Japanese and English fluently to interact with internal and external stakeholders. Preferred qualifications: Master’s degree or PhD in AI, Computer Science, or a related technical field. Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s ADK) and patterns like ReAct, self-reflection, and hierarchical delegation. Knowledge of Large Language Model (LLM) native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing. About the jobAs a Generative AI Forward Deployed Engineer (FDE) at Google Cloud, you will be an embedded builder who bridges the gap between frontier AI products and production-grade reality within customer environments. Unlike traditional advisory roles, you will function as an innovator builder moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment. You will address blockers to production, including solving the integration complexities, data readiness issues, and state-management issues that prevent AI from reaching enterprise-grade maturity. By embedding with accounts, you will serve a dual purpose providing white-glove deployment of AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours.Responsibilities Serve as a developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol servers) that drive Return on Investment (ROI). Architect and code the connective tissue between Google’s AI products and customers live infrastructure, including APIs, legacy data silos, and security perimeters as part of an expert team. Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency. Identify repeatable field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams. Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Established in 1987 and headquartered in Taiwan, TSMC pioneered the pure-play foundry business model with an exclusive focus on manufacturing its customers’ products. As of 2024, TSMC serves more than 500 customers and manufactures over 11,000 products for high-performance computing, smartphones, the Internet of Things (IoT), automotive, and digital consumer electronics. It is the world’s largest provider of logic ICs, with an annual capacity of 16 million 12-inch equivalent wafers. TSMC operates fabs in Taiwan as well as manufacturing subsidiaries in Washington State, Japan and China, and the Company began construction on a specialty technology fab in Dresden, Germany, in 2024. In Arizona, TSMC is building three fabs, with the first starting 4nm production in 2025, the second by 2028, and the third by the end of the decade. The AI4BI team serves as the central intelligence hub within the Corporate Planning Organization (CPO). Our mission is to empower business users with AI-driven solutions that enhance customer satisfaction and streamline operational efficiency. We work closely with stakeholders who blend deep domain expertise in areas like demand and capacity planning with strong analytical capabilities.As an AI Engineer in the Product Innovation department, you will collaborate closely with product managers, designers, and internal business users to prototype and integrate new features into products. You are self-motivated and naturally curious, driven to innovate and deliver impactful results. Responsibilities: 1. Drive Innovation and Impact: Pioneer novel AI/ML solutions from initial concept to functional prototype. Shape the future of our internal product with your discoveries.2. Collaborate with Business Users: Work closely with internal stakeholders to understand needs and translate them into actionable AI-driven solutions that create measurable value.3. Apply Smart AI Techniques: Choose and implement the appropriate methods—classic machine learning, deep learning, or generative AI—to effectively solve diverse problems.4. Partner Across Teams and Geographies: Collaborate with cross-functional, global teams including AI researchers, engineers, and domain experts to integrate AI into production systems.5. Share Knowledge and Stay Current: Communicate insights through data storytelling, mentor colleagues, and proactively adopt emerging AI/ML trends to continuously improve solutions.

MoMo is Vietnam’s leading financial super-app, redefining how millions manage their money through AI-driven innovation. Our Big Data AI Team doesn’t just support the product—we are the product. From hyper-personalization and eKYC to fraud detection, AI is the heartbeat of MoMo.As a Senior AI Engineer, you will lead the evolution of our Generative AI ecosystem. You won’t just be prompting LLMs; you’ll be architecting sophisticated Agentic workflows and productionizing state-of-the-art models that serve millions of users in real-time.Mô tả công việcLead Architecture: Design and deploy scalable Agentic frameworks and Generative AI solutions that integrate seamlessly into the MoMo ecosystem;Production-Grade AI: Build and maintain robust LLM-based products using SOTA techniques (RAG, fine-tuning, and prompt orchestration) and open-source libraries;Cross-Functional Leadership: Partner with Data Scientists, Backend Engineers, and Product Managers to bridge the gap between experimental models and high-availability production systems;Engineering Excellence: Write clean, high-performance production code and establish best practices for LLM Ops (CI/CD for models, versioning, and monitoring);Evaluation Optimization: Define rigorous evaluation metrics (faithfulness, relevancy, latency) and conduct A/B experiments to iterate on model performance;Scale: Optimize AI systems to handle high-concurrency traffic while maintaining low latency.Yêu cầu công việcExperience: 3+ years in professional software/AI engineering, with a deep focus on Voice Agentic and Generative AI;LLM Mastery: Hands-on experience with model families like Llama 3, Qwen 2, GPT-4, and BERT. You understand their architectures, tokenization nuances, and limitations;System Design: Proven track record of building Agentic systems or Voice-AI from scratch—taking them from preprocessing to real-world drift monitoring;Tech Stack: Mastery of Python and deep learning frameworks (PyTorch or TensorFlow). Experience with vector databases (Milvus, Pinecone, or similar) is a plus;Mindset: A product-oriented engineer who cares about the "Why" as much as the "How."

Minimum qualifications: Bachelor's degree or equivalent practical experience. 5 years of experience managing projects and defining project scope, goals, and deliverables. 5 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data. Preferred qualifications: Experience working with Google's products and services (e.g., generative AI products). Experience in SQL, building dashboards, data collection/transformation, or visualization/dashboards or experience in a scripting/programming language (e.g., Python). Knowledge of content moderation policies and best practices. Excellent problem-solving skills with attention to detail in an ever-changing environment. About the jobTrust Safety team members are tasked with identifying and taking on the biggest problems that challenge the safety and integrity of our products. They use technical know-how, excellent problem-solving skills, user insights, and proactive communication to protect users and our partners from abuse across Google products like Search, Maps, Gmail, and Google Ads. On this team, youre a big-picture thinker and strategic team-player with a passion for doing what’s right. You work globally and cross-functionally with Google engineers and product managers to identify and fight abuse and fraud cases at Google speed - with urgency. And you take pride in knowing that every day you are working hard to promote trust in Google and ensuring the highest levels of user safety. As a Senior Engineering Analyst, you'll play a crucial role in ensuring a safe and trusted experience for users interacting with AI features in Google Photos. You will work directly with Product Management, Engineering, Policy, and Legal teams to build and execute a comprehensive approach to push the AI model to its limits and build resilience against malicious or unexpected inputs.At Google we work hard to earn our users’ trust every day. Trust Safety is Google’s team of abuse fighting and user trust experts working daily to make the internet a safer place. We partner with teams across Google to deliver bold solutions in abuse areas such as malware, spam and account hijacking. A team of Analysts, Policy Specialists, Engineers, and Program Managers, we work to reduce risk and fight abuse across all of Google’s products, protecting our users, advertisers, and publishers across the globe in over 40 languages.Responsibilities Accelerate generative AI feature development by preparing comprehensive and automated trust and safety evaluations set across all relevant data types/languages and that cover all critical generative AI user journeys (e.g., edits, search, etc.). Conduct research, identify emerging risk areas, abuse vectors, and edge cases, and build internal and external partnerships for generative AI safety. Partner with product, engineering, policy, research, central trust and safety, etc. to develop tailored testing approaches, tools, and solutions (e.g., test accounts etc.), test execution, and model output analysis to inform improvement areas and safety mechanisms. Establish testing to discover residual and emergent risks. Define program metrics and communication, and establish health metrics and feedback loops with stakeholders to evolve the program and report on key insights. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Role PurposeAs an Applied AI Engineer, you design and deliver practical AI solutions that improve efficiency, quality, and scalability within ASML Customer Support.Your focus is on applying AI and Generative AI in real operational environments, turning business needs into AI solutions that are reliable, secure, and ready for daily use.This role sits at the intersection of AI, software solutions, and business operations, working closely with IT, engineers, and business stakeholders.Key ResponsibilitiesApplied AI Solution DevelopmentDesign and build AI‑driven solutions that support process improvement, intelligent diagnostics, and decision support.Apply Generative AI and agent‑based AI concepts to automate and simplify complex workflows.Translate operational challenges into practical, usable AI solutions that deliver measurable business value.Software Platform EngineeringBuild AI solutions in a clear and structured way, so they are easy to understand, update, and support over time.Ensure AI solutions run on ASML‑approved systems and data platforms, not personal tools or one‑off scripts.Work together with IT and platform teams so solutions are stable, secure, and suitable for daily operations.Make sure solutions are reliable, protect sensitive data, and can be maintained or improved by others in the future.Stakeholder CollaborationCollaborate with IT teams, software engineers, and business stakeholders to align AI solutions with business needs and company standards.Explain AI concepts and solution choices in a clear, practical, and non‑technical way when needed.Act as a bridge between business problems and technical solutions.Adoption Continuous ImprovementSupport the adoption and scaling of AI solutions across teams.Continuously follow developments in AI, Generative AI, and automation, and propose improvements relevant to ASML.Contribute to a culture of continuous improvement and learning.Education ExperienceBachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, or a related field.5+ years of experience in software development or automation‑related roles.3+ years of experience applying AI or data‑driven solutions in an enterprise or industrial environment.Experience working with cloud or enterprise data platforms is preferred.Knowledge SkillsCore SkillsStrong problem‑solving mindset and ability to translate ideas into working solutions.Practical experience implementing RAG‑based AI solutions, including document retrieval, ranking, and AI‑assisted response generation.Familiarity with vector search, embeddings, or knowledge‑based AI systems used in enterprise environments.Experience creating reports, dashboards, or insights using tools such as Power BI, Tableau, or Excel.Professional CompetenciesClear communication with both technical and non‑technical stakeholders.Structured and disciplined way of working.Strong ownership mindset and ability to work independently.Willingness to learn and adapt in a fast‑evolving AI landscape.Nice to HaveKnowledge of ASML products, diagnostics tools, or customer support processes.Experience working with industrial, operational, or machine data.Awareness of data security, compliance, and enterprise governance.This position requires access to controlled technology, as defined in the United States Export Administration Regulations (15 C.F.R. § 730, et seq.). Qualified candidates must be legally authorized to access such controlled technology prior to beginning work. Business demands may require ASML to proceed with candidates who are immediately eligible to access controlled technology.Inclusion and diversityASML is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that inclusion and diversity is a driving force in the success of our company.Need to know more about applying for a job at ASML? Read our frequently asked questions.

Minimum qualifications: Bachelor’s degree or equivalent practical experience. 5 years of experience in software development. 5 years of experience with testing or launching software products. 5 years of experience with speech/audio, reinforcement learning, or Machine Learning (ML) infrastructure. 3 years of experience with software design/architecture. Experience with Generative AI (GenAI) concepts (e.g., Large Language Model (LLM), multi-modal, large vision models). Preferred qualifications: Master’s degree or PhD in Engineering or Computer Science. 3 years of experience in technical leadership with leading project teams. Experience in Vertex AI, BigQuery, Cloud Storage, and Dialogflow. About the jobGoogle Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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. The Applied AI (AAI) organization is Google Cloud's engine for transforming business with groundbreaking packaged generative Artificial Intelligence (AI) solutions. The team focuses on turning business challenges into reasoning-based AI solutions that drive rapid, measurable business growth. Our product portfolio includes the Gemini Enterprise for Customer Engagement suite which offers prebuilt and configurable agents developed using Google’s Gemini models to help businesses transform the entire customer lifecycle from initial product discovery to post-purchase resolution along with many other domain-specific enterprise AI applications.The AAI Solutions Consulting Team is the unit at the epicenter of this work. The team is the technical engine defining the best practices and deployment frameworks that will set the standard for building and deploying enterprise AI agents at scale across the Google Cloud ecosystem. We ensure nascent AI capabilities translate into enterprise reality, helping customers navigate the transition from legacy stacks to GenAI-native architectures. We are the team that synchronizes Solution Architecture, Engineering, and Product to move AI agents from discovery to high-scale production. We operate with the velocity and intensity of a startup environment. In this role, you will take product ideas from conception to full-scale production in weeks and help enterprise customers adopt and deploy AI with the speed they crave. You will be a flexible and proficient AI agent builder ready to define the job. You will move between high-level systems thinking and execution. You will be willing to manage new processes and quality checks, and the critical work of front-line execution. You will evolve, and be energized by ambiguity and eagerness to flex into new areas as the business changes.Responsibilities Partner with customers to design, co-develop, debug, and deploy Artificial Intelligence (AI) agents and solutions. Act as a problem solver, empowered to write codes, develop custom tooling, and contribute to the core product codebase. Systematize learnings from customer engagements while working with AI team members to create reusable tools, documentation, and accelerators. Serve as a feedback loop to core Product and Engineering teams, synthesizing field insights to influence strategy. Provide technical guidance on agent improvement, performance tuning, Continuous Integration/Continuous Deployment (CI/CD) pipelines, and production readiness. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Hyderabad, Telangana, India; Bengaluru, Karnataka, India; Gurugram, Haryana, India.Minimum qualifications: Bachelor’s degree or equivalent practical experience. 5 years of experience with the Google Ads ecosystem and its products. Experience using AI-powered tools for content creation. Preferred qualifications: Experience integrating content strategy with product and engineering roadmaps, with the ability to influence others and to communicate and collaborate well with cross-functional teams. Understanding of Generative AI guardrails, including identifying and mitigating risks like hallucinations or grounding issues, to ensure that AI-driven solutions provide a consistently reliable, accurate, and high-quality experience for Google’s users and partners.Strong understanding of content strategy, knowledge management principles, and data analysis. Ability to independently manage multiple, time-sensitive project schedules and identify and mitigate risks. About the jobGoogle Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.Responsibilities Own the content strategy within a specific product area, aligning content development with product roadmaps and prioritizing launches. Turn business goals into content solutions. Drive the success of AI-powered solutions by mapping user intent to specific content solutions. You will translate business requirements into precise AI instructions (prompts) and monitor model behavior to ensure responses are grounded in fact and aligned with Ads product logic. Develop and refresh high-quality content solutions (text, video, interactive AI) for top user issues and customer journeys within your priority product areas. Engage with cross-functional forums (Product Circles, CoE, etc.) to integrate content strategy with broader product-specific initiatives. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.