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MoMo is the market leader in mobile payments in Vietnam. We strive to make all transactions fast, easy and joyful. We are looking for an experienced AI Engineer to join our growing Big Data AI team. At MoMo, we make AI/Machine Learning the core component to almost every part of the product - product recommendation, personalization, conversational AI, eKYC, risk scoring, fraud detection, promotion targeting and financial services. As a Senior AI Engineer, you will play a leading role in developing our Customer Service Chatbot system, delivering intelligent and seamless support experiences to millions of users.Mô tả công việcDesign, build, and optimize LLM-powered chatbot systems for customer service at scale;Develop and implement RAG (Retrieval-Augmented Generation) pipelines, prompt engineering strategies, and agentic workflows for domain-specific performance;Architect conversation flows, intent handling, and dialogue management systems that handle complex multi-turn interactions;Build evaluation frameworks and monitoring systems to measure chatbot quality, detect hallucinations, and ensure response accuracy;Collaborate cross-functionally with product, customer service operations, and engineering teams to continuously improve chatbot capabilities;Write production-grade code and maintain robust, scalable AI systems serving millions of users;Stay current with LLM advancements and evaluate new models, techniques, and tools for potential adoption.Yêu cầu công việc5+ years of experience as an AI Engineer, with at least 2 years focused on LLM applications or conversational AI systems;Deep understanding of LLM architectures, capabilities, and limitations (GPT, Claude, LLaMA, etc.);Experience building chatbot or virtual assistant systems, particularly for customer service use cases;Fintech domain experience is a strong plus;Proficiency in RAG systems, vector databases, embedding models, and prompt engineering techniques;Strong software engineering skills in Python. Experience with LLM tooling (LangChain, LlamaIndex, etc.);Experience with system design for high-availability, low-latency services;Familiarity with evaluation methods for generative AI systems and conversation quality metrics.

Req ID: 134791Remote Position: HybridRegion: EuropeCountry: United KingdomGeneral OverviewFunctional Area: Information Technology (ITM)Career Stream: IT SolutionsRole: Technical Lead (TEL)Job Title: Technical Lead, IT SolutionsJob Code: TL-ITM-SOLNJob Level: Level 10Direct/Indirect Indicator: IndirectSummaryWe are seeking a highly motivated and technically proficient AI Engineer to join our growing Data Analytics team. In this role, you will be a key liaison between business stakeholders and the technical AI team, translating complex business challenges into scalable artificial intelligence and machine learning solutions. You will be responsible for defining technical requirements, designing AI architectures (including Generative AI and RAG patterns), and collaborating with the Data Center of Excellence to deliver high-quality, production-ready AI tools that drive innovation and operational efficiency across the organization.Detailed DescriptionAI Solution Scoping Requirements:•Elicit and document technical requirements for AI and Machine Learning projects through workshops and deep dives with stakeholders across various departments.•Define the technical feasibility of proposed AI use cases, identifying appropriate model architectures (LLMs, SLMs, or traditional ML) and success metrics (Accuracy, F1-score, Perplexity, etc.).•Analyze existing business processes to identify automation opportunities and areas where Generative AI can provide a competitive advantage.Data Engineering AI Pipeline Design:•Work with stakeholders to identify and prepare high-quality datasets for model training, fine-tuning, and grounding.•Design and implement data ingestion pipelines for vector databases, ensuring data integrity and optimal embedding strategies for Retrieval-Augmented Generation (RAG).•Collaborate with data engineers to ensure scalable, secure, and compliant data flows between enterprise systems and AI models.Model Development Orchestration:•Develop, test, and refine AI prompts and orchestration workflows using frameworks like LangChain, LlamaIndex, or Semantic Kernel.•Evaluate and select appropriate foundation models (OpenAI, Anthropic, Llama, etc.) based on performance, cost, and latency requirements.•Translate business logic into technical specifications for API integrations, model endpoints, and user interfaces.MLOps, Deployment Monitoring:•Implement MLOps best practices to ensure the continuous integration and deployment (CI/CD) of AI models.•Establish monitoring frameworks to track model performance, "drift," and hallucination rates in production environments.•Ensure AI solutions adhere to corporate data governance, security, and ethical AI principles.Knowledge/Skills/Competencies•Essential Skills:•11+ years of experience in Information Technology, Software Engineering, or Data Science, with a significant focus on AI/ML development.•Strong understanding of Generative AI landscapes, including LLMs, prompt engineering, and vector databases (e.g., Pinecone, Weaviate, Milvus).•Proven ability to architect end-to-end AI solutions from discovery to production deployment.•Excellent communication skills, with the ability to explain complex technical AI concepts to non-technical business leaders.•Advanced proficiency in Python and relevant libraries (NumPy, Pandas, PyTorch, or TensorFlow).•Experience with Cloud AI Services (Azure AI Studio, AWS Bedrock, or Google Vertex AI [Preferred]).Desirable Skills:•Knowledge of SQL and advanced data modeling for structured and unstructured data.•Familiarity with MLOps tools (MLflow, Kubeflow) and containerization (Docker, Kubernetes).•Experience working in an Agile/Scrum development environment.•Knowledge of AI security frameworks and responsible AI practices (e.g., OWASP for LLMs, MCP).•Industry experience in manufacturing or a related industrial sector.Physical Demands• Duties of this position are performed in a normal office environment.• Duties may require extended periods of sitting and sustained visual concentration on a computer monitor or on numbers and other detailed data. Repetitive manual movements (e.g., data entry, using a computer mouse, using a calculator, etc.) are frequently required.Typical Experience•11+ years of progressive experience in technical roles, with at least 3-5 years specifically focused on AI/ML engineering or architecture.•Proven track record of delivering production-grade AI applications.•AI-related certifications (e.g., Azure AI Engineer Associate, AWS Machine Learning Specialty) are highly preferred.Typical Education• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, or a related field; or a robust combination of work experience and specialized AI certification.NotesThis job description is not intended to be an exhaustive list of all duties and responsibilities of the position. Employees are held accountable for all duties of the job. Job duties and the % of time identified for any function are subject to change at any time.Celestica is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws.This policy applies to hiring, promotion, discharge, pay, fringe benefits, job training, classification, referral and other aspects of employment and also states that retaliation against a person who files a charge of discrimination, participates in a discrimination proceeding, or otherwise opposes an unlawful employment practice will not be tolerated. All information will be kept confidential according to EEO guidelines.Celestica is an E-Verify employer.Location: This is a remote position, with travel as necessary. We are open to considering candidates close to any of our US locations in Massachusetts, Pennsylvania, Minnesota, Texas, Arizona, Oregon or California as well as locations near major airports such as the Northeast, Southeast, Midwest and Pacific Coast.COMPANY OVERVIEW:Celestica (NYSE, TSX: CLS) enables the world’s best brands. Through our recognized customer-centric approach, we partner with leading companies in Aerospace and Defense, Communications, Enterprise, HealthTech, Industrial, Capital Equipment and Energy to deliver solutions for their most complex challenges. As a leader in design, manufacturing, hardware platform and supply chain solutions, Celestica brings global expertise and insight at every stage of product development – from drawing board to full-scale production and after-market services for products from advanced medical devices, to highly engineered aviation systems, to next-generation hardware platform solutions for the Cloud.Headquartered in Toronto, with talented teams spanning 40+ locations in 13 countries across the Americas, Europe and Asia, we imagine, develop and deliver a better future with our customers.Celestica would like to thank all applicants, however, only qualified applicants will be contacted.Celestica does not accept unsolicited resumes from recruitment agencies or fee based recruitment services.

Req ID: 132986Remote Position: HybridRegion: AmericasCountry: USAGeneral OverviewFunctional Area: Information Technology (ITM)Career Stream: IT SolutionsRole: Technical Lead (TEL)Job Title: Technical Lead, IT SolutionsJob Code: TL-ITM-SOLNJob Level: Level 10Direct/Indirect Indicator: IndirectSummaryWe are seeking a highly motivated and technically proficient AI Engineer to join our growing Data Analytics team. In this role, you will be a key liaison between business stakeholders and the technical AI team, translating complex business challenges into scalable artificial intelligence and machine learning solutions. You will be responsible for defining technical requirements, designing AI architectures (including Generative AI and RAG patterns), and collaborating with the Data Center of Excellence to deliver high-quality, production-ready AI tools that drive innovation and operational efficiency across the organization.Detailed DescriptionAI Solution Scoping Requirements:•Elicit and document technical requirements for AI and Machine Learning projects through workshops and deep dives with stakeholders across various departments.•Define the technical feasibility of proposed AI use cases, identifying appropriate model architectures (LLMs, SLMs, or traditional ML) and success metrics (Accuracy, F1-score, Perplexity, etc.).•Analyze existing business processes to identify automation opportunities and areas where Generative AI can provide a competitive advantage.Data Engineering AI Pipeline Design:•Work with stakeholders to identify and prepare high-quality datasets for model training, fine-tuning, and grounding.•Design and implement data ingestion pipelines for vector databases, ensuring data integrity and optimal embedding strategies for Retrieval-Augmented Generation (RAG).•Collaborate with data engineers to ensure scalable, secure, and compliant data flows between enterprise systems and AI models.Model Development Orchestration:•Develop, test, and refine AI prompts and orchestration workflows using frameworks like LangChain, LlamaIndex, or Semantic Kernel.•Evaluate and select appropriate foundation models (OpenAI, Anthropic, Llama, etc.) based on performance, cost, and latency requirements.•Translate business logic into technical specifications for API integrations, model endpoints, and user interfaces.MLOps, Deployment Monitoring:•Implement MLOps best practices to ensure the continuous integration and deployment (CI/CD) of AI models.•Establish monitoring frameworks to track model performance, "drift," and hallucination rates in production environments.•Ensure AI solutions adhere to corporate data governance, security, and ethical AI principles.Knowledge/Skills/Competencies•Essential Skills:•11+ years of experience in Information Technology, Software Engineering, or Data Science, with a significant focus on AI/ML development.•Strong understanding of Generative AI landscapes, including LLMs, prompt engineering, and vector databases (e.g., Pinecone, Weaviate, Milvus).•Proven ability to architect end-to-end AI solutions from discovery to production deployment.•Excellent communication skills, with the ability to explain complex technical AI concepts to non-technical business leaders.•Advanced proficiency in Python and relevant libraries (NumPy, Pandas, PyTorch, or TensorFlow).•Experience with Cloud AI Services (Azure AI Studio, AWS Bedrock, or Google Vertex AI [Preferred]).Desirable Skills:•Knowledge of SQL and advanced data modeling for structured and unstructured data.•Familiarity with MLOps tools (MLflow, Kubeflow) and containerization (Docker, Kubernetes).•Experience working in an Agile/Scrum development environment.•Knowledge of AI security frameworks and responsible AI practices (e.g., OWASP for LLMs, MCP).•Industry experience in manufacturing or a related industrial sector.Physical Demands• Duties of this position are performed in a normal office environment.• Duties may require extended periods of sitting and sustained visual concentration on a computer monitor or on numbers and other detailed data. Repetitive manual movements (e.g., data entry, using a computer mouse, using a calculator, etc.) are frequently required.Typical Experience•11+ years of progressive experience in technical roles, with at least 3-5 years specifically focused on AI/ML engineering or architecture.•Proven track record of delivering production-grade AI applications.•AI-related certifications (e.g., Azure AI Engineer Associate, AWS Machine Learning Specialty) are highly preferred.Typical Education• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, or a related field; or a robust combination of work experience and specialized AI certification.NotesThis job description is not intended to be an exhaustive list of all duties and responsibilities of the position. Employees are held accountable for all duties of the job. Job duties and the % of time identified for any function are subject to change at any time.Celestica is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws.This policy applies to hiring, promotion, discharge, pay, fringe benefits, job training, classification, referral and other aspects of employment and also states that retaliation against a person who files a charge of discrimination, participates in a discrimination proceeding, or otherwise opposes an unlawful employment practice will not be tolerated. All information will be kept confidential according to EEO guidelines.Celestica is an E-Verify employer.Location: This is a remote position, with travel as necessary. We are open to considering candidates close to any of our US locations in Massachusetts, Pennsylvania, Minnesota, Texas, Arizona, Oregon or California as well as locations near major airports such as the Northeast, Southeast, Midwest and Pacific Coast.COMPANY OVERVIEW:Celestica (NYSE, TSX: CLS) enables the world’s best brands. Through our recognized customer-centric approach, we partner with leading companies in Aerospace and Defense, Communications, Enterprise, HealthTech, Industrial, Capital Equipment and Energy to deliver solutions for their most complex challenges. As a leader in design, manufacturing, hardware platform and supply chain solutions, Celestica brings global expertise and insight at every stage of product development – from drawing board to full-scale production and after-market services for products from advanced medical devices, to highly engineered aviation systems, to next-generation hardware platform solutions for the Cloud.Headquartered in Toronto, with talented teams spanning 40+ locations in 13 countries across the Americas, Europe and Asia, we imagine, develop and deliver a better future with our customers.Celestica would like to thank all applicants, however, only qualified applicants will be contacted.Celestica does not accept unsolicited resumes from recruitment agencies or fee based recruitment services.

About BTSE: BTSE Groupis a global leader in fintech and blockchain technology, anchored by three core business pillars: Exchange, Payments, and Infrastructure Development. Serving over 100 corporate clients worldwide, we provide white-label exchange and payment solutions. Our offerings encompass everything from exchange infrastructure hosting and development to custody, wallets, payments, blockchain integration, trading, and more.We are looking for talented professionals in marketing, operations, customer support, and other departments. The roles offered may be on-site, remote, or hybrid, in collaboration with our local partner. About the Opportunity: As the AI Business Strategy Manager, you will be the primary architect of BTSE’s transformation into an AI-first organization. Reporting directly to the Head of Operations, you will bridge the gap between high-level strategic vision and technical execution.Responsibilities Strategic Roadmap Ownership: Architect and lead the enterprise AI implementation strategy, ensuring every initiative is purpose-built to meet 2026 goals for platform protection and operational excellence. Departmental Advisory: Partner with the Heads of Operations and other department heads to diagnose workflow friction and design autonomous, "Agentic" solutions that streamline cross-functional output. AI Performance Governance: Establish and own the framework for AI ROI by defining and tracking high-stakes KPIs, including Token Efficiency, HITL (Human-in-the-Loop) reduction, and Automated Resolution Accuracy. Security Risk Collaboration: Co-engineer AI-driven defense layers with the Security team to proactively neutralize platform threats, specifically targeting anti-bot measures and mass-registration blocking. Technical Architecture Design: Translate high-level strategic designs into scalable technical assets, including robust API integrations, standardized prompt libraries, and MCP (Model Context Protocol) servers. Operational Excellence: Oversee the end-to-end lifecycle of AI deployments to ensure designs are not only innovative but also functional, secure, and seamlessly integrated into the enterprise ecosystem. Requirements A proven track record in AI strategy, demonstrating a clear evolution from early LLM applications to sophisticated RAG (Retrieval-Augmented Generation) and Agentic Workflows. Deep experience in high-growth Fintech or Crypto environments, with a demonstrated ability to scale operations while maintaining rigorous security standards. While business-led, you are fluent in the "language of engineering," comfortable discussing API orchestration, Vector Databases, and Model Context Protocols (MCP) with technical teams. A sophisticated influencer capable of navigating complex organizational structures to lead departments through the cultural and technical shifts of AI adoption. Professional fluency in English is essential; proficiency in Chinese is highly advantageous to facilitate seamless communication across our global teams. A data-driven mindset with the ability to translate technical performance metrics into clear business outcomes and executive-level insights. Perks Benefits Competitive compensation package Various team-building programs and company events Comprehensive healthcare schemes for employees and dependants And many more! Apply and let us tell you more! #LI-PP1

Minimum qualifications: Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience. 5 years of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume). Experience managing client-facing projects, troubleshooting technical issues, and working with engineering and sales services teams. Preferred qualifications: Experience building data pipelines specifically for AI agents, vector databases, or feature stores. Experience managing data privacy and compliance in a highly regulated or large-scale corporate environment. Strong understanding of data infrastructure concepts and ability to layout policies for a foundational data layer. Familiarity with Google Cloud’s data stack (BigQuery, Dataflow, Pub/Sub, Vertex AI). Ability to translate executive-level business requirements into technical data architectures. About the jobThe Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses grow. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners. The Central Tooling and Analytics team is the operational backbone of Google Cloud’s efficiency. We specialize in engineering high-impact tools and streamlined workflows designed to reduce manual toil and improve decision making. At the core of our tooling and analytics strategy, the Central Data Engineering team aims to provide high-quality signals required to power agentic workflows and AI-driven automation across the organization curating data across many critical pillars like programs, products and people.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s 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 Own the foundational design of the WISE data layer. Architect the environment to be AI-native, ensuring it supports both high-performance analytics and the low-latency requirements of Large Language Model (LLM) based agents. Design and implement sophisticated data policies, Identity and Access Management (IAM) protocols, and environment management strategies to ensure secure, multi-tenant access. Scope and design sophisticated data models for complex, intersecting domains (people, spend, objectives and key results, and programs). Ensure these models serve as the definitive Single Source of Truth (SSoT) for Google Cloud Platform (GCP) leadership. Translate business logic into agentic-ready datasets. Optimize data structures specifically for Retrieval-Augmented Generation (RAG), vector embeddings, and tool-use by AI agents. Onboard new domains (product, commercial metrics) while constantly refreshing the existing domains. 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.

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform. WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers and portfolio managers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people. The Role: We are building a new software engineering team with strong applied AI orientation to amplify WorldQuant's success. The team is focusing on creating company-wide applications to address our colleagues’ every day problems. You will have a chance to work with a broad range of teams at WorldQuant, helping them to be more productive with custom solutions. Collaborate with cross-functional distributed teams. Gather, analyze and spec out requirements, and manage product deliverables. Design and build scalable AI-driven products addressing real-world problems. Stay current with the latest technical advancements, particularly in the field of AI and LLMs. What You’ll Bring: Strong programming skills, preferably in Python. Exceptional analytical skills and a passion for solving complex problems. Thorough understanding of how AI works and familiarity with language models. Understanding of vector databases and other relevant data structures. Working knowledge in various databases and messaging technologies is a strong plus. (SQL, Redis, Kafka etc.) Excellent communication skills in English. Mature, thoughtful attitude with the ability to operate in a collaborative, team-oriented culture. A strong delivery mind-set, drive to get things done. Experience in finance is not required. #LI-MH1 By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction. Copyright © 2025 WorldQuant, LLC. All Rights Reserved.WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform. WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers and portfolio managers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people. The Role: We are building a new software engineering team with strong applied AI orientation to amplify WorldQuant's success. The team will be focusing on creating company-wide applications to address our colleagues’ every day problems. You will have a chance to work with a broad range of teams at WorldQuant, helping them to be more productive with custom solutions. Collaborate with cross-functional distributed teams. Gather, analyze and spec out requirements, and manage product deliverables. Design and build scalable AI-driven products addressing real-world problems. Stay current with the latest technical advancements, particularly in the field of AI and LLMs. What You’ll bring: Strong programming skills, preferably in Python. Exceptional analytical skills and a passion for solving complex problems. Thorough understanding of how AI works and familiarity with language models. Understanding of vector databases and other relevant data structures. Working knowledge in various databases and messaging technologies is a strong plus. (SQL, Redis, Kafka etc.) Excellent communication skills in English. Mature, thoughtful attitude with the ability to operate in a collaborative, team-oriented culture. A strong delivery mind-set, drive to get things done. Experience in finance is not required. What We Offer: Competitive compensation package Core benefits include: premium private health insurance and life insurance with savings plan Support for every aspect of life through Employee Assistance Program and fully covered sick leave Strong culture of learning and development: training courses, library, guest speakers, share and learn events, global conferences Regular offsite team buildings, annual conferences and occasional global summits – opportunity to travel and connect with our local and global teams #LI-MH1By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction. Copyright © 2025 WorldQuant, LLC. All Rights Reserved.WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.

Google welcomes people with disabilities.Minimum qualifications: Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience. 2 years of experience with software development using Python or similar coding languages. Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., GCP). Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions. Ability to communicate in Korean and English fluently to conduct necessary business interaction in Korean and English. 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, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation). Experience leading technical discovery sessions. 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 will be an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. 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. This role is designed for high-agency engineers with a founder’s mindset. 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 as 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 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 complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable 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 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.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mumbai, Maharashtra, India; Bengaluru, Karnataka, India; Hyderabad, Telangana, India.Minimum qualifications: Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience. 5 years of experience with software development using Python or similar coding languages. Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., GCP). Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions. Experience leading technical discovery sessions. Preferred qualifications: Master’s or PhD in AI, Computer Science, or a related technical field. Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, 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. This role is designed for high-agency engineers with a founder’s mindset. You will address 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 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 complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable 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 rigorous 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.

Minimum qualifications: Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience. 8 years of experience in cloud computing or a technical customer-facing role. Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., GCP). Experience building pipelines for structured and unstructured data using both vector databases and Retrieval-Augmented Generation (RAG)-like architectures to power enterprise AI solutions. Experience leading technical discovery sessions. 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, Agent Development Kit (ADK)) and complex patterns (e.g., ReAct, self-reflection, 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 will be an embedded builder who bridges the gap between frontier Artificial Intelligence (AI) products and production-grade reality within customers. 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 challenges that prevent AI from reaching enterprise-grade maturity. You serve will 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 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 complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, Model Context Protocol (MCP) servers) that drive measurable Return on Investment (ROI). Architect and code the "connective tissue" between Google’s AI products and customer's live infrastructure, including Application Programming Interfaces (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 rigorous 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.