Senior Ai Engineer: Autonomous Agents (Remote Latam)
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Descripción de la vacante
Google Cloud is hiring a Senior ML/AI Engineer to design and implement agentic AI workflows, leveraging RAG, vector databases, and LLM APIs. This role supports cloud security automation, Terraform and Rego policy integration, and collaboration with global teams in a remote setup from Argentina.
You will drive AI accelerations, build compliant IaC modules, and contribute to customer-facing ML solutions using Google’s TensorFlow, Vertex AI, and related tools.
Formación
- Bachelor's degree in Computer Science or equivalent practical experience.
- 3 years building ML solutions and working with technical customers.
- Experience designing cloud enterprise solutions and supporting customer projects.
- Experience building and deploying custom ML models into production, including agentic AI workflows.
- Ability to communicate in English fluently as this is a customer-facing role.
Responsabilidades
- Be a trusted technical advisor to customers and solve complex ML challenges.
- Coach customers on practical challenges in ML systems: feature extraction, data validation, monitoring, and management of features and models.
- Work with Customers, Partners, and Google Product teams to deliver tailored solutions into production.
- Create and deliver best practice recommendations, tutorials, blog articles, and sample code.
- Travel up to 30% in-region for meetings, technical reviews, and onsite delivery activities.
Conocimientos
Educación
Herramientas
Descripción del empleo
AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
We are looking for an Agentic AI Engineer to build generative AI workflows that automate cloud configuration baselines and remediation.
The mandatory requirements are 4+ years of software engineering experience on public cloud infrastructure, 2+ years with cloud deployment pipelines and Infrastructure as Code, 2+ years developing agentic models using RAG and vector databases, and the ability to partner with globally distributed engineering teams.
- 4+ years of software engineering experience developing applications and services hosted on public cloud infrastructure.
- 2+ years of experience with cloud infrastructure deployment pipelines and infrastructure as code (IaC).
- 2+ years of experience developing Agentic models (e.g., OpenAI, Anthropic) using Retrieval-Augmented Generation (RAG) and Vector databases.
- Proven capability to partner with globally distributed inter-disciplinary engineering teams.
- Hands-on experience with modern AI orchestration frameworks (LangChain, LangGraph).
- Hands-on experience writing Rego policies (Open Policy Agent) or Regula test cases.
- Hands-on experience with Terraform.
- Familiarity with cloud-native security services in Amazon Web Services, Azure, and Google Cloud Platform.
- Familiarity with PagerDuty, Atlassian Suite, and Service Now.
- AI Acceleration: implement generative AI workflows utilizing RAG, vector databases, and LLM APIs to automate the creation of cloud configuration baselines.
- Cloud Security Automation: develop AI-enabled drift detection, continuous discovery, and gap analysis capabilities to accelerate response and remediation activities.
- Policy & Infrastructure as Code (IaC): generate and validate compliant Terraform modules, Rego policies (for Wiz Custom Configuration Rules), and Regula test cases for CI/CD pipelines.
- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
- Exciting projects: Modern solutions with Fortune 500 and top product companies.
- Flextime: Flexible schedule with remote and office options.
LangChain.
LangGraph.
AWS.
- Toolkits RAG: LangChain Retrievers, LlamaIndex integrations. Entorno Cloud & Serverless GenAI
Cloud AI Engineer, Google Cloud (English) Share Cloud AI Engineer, Google Cloud (English)
_corporate_fare_ Google _place_ Mexico City, CDMX, Mexico; Buenos Aires, Argentina
**Early**
Experience completing work as directed, and collaborating with teammates; developing knowledge of relevant concepts and processes.
Share Cloud AI Engineer, Google Cloud (English)
_info_outline_
X
In most instances, this position requires in-person interviews as part of the hiring process.
**Minimum qualifications:
- Bachelor's degree in Computer Science or equivalent practical experience.
- Experience building machine learning solutions and working with technical customers.
- Experience designing cloud enterprise solutions and supporting customer projects to completion.
- Experience building and deploying custom ML models into production, including experience with deep learning frameworks and with designing and deploying agentic AI workflows for business process automation.
- Experience coding in Python, including data structures, algorithms, and software design.
- Ability to communicate in English fluently as this is a customer-facing role.
**Preferred qualifications:
- Experience with recommendation engines, data pipelines, distributed machine learning, and deep learning frameworks.
- Experience in data analytics, data visualization techniques, and core Data Science methodologies.
- Experience in software development, professional services, or technical consulting for new technology initiatives.
- Knowledge of data warehousing (ETL/ELT), technical architectures, and big data environments (e.g., Hadoop, Spark).
- Knowledge of cloud computing, including virtualization, multi-tenant infrastructures, and storage systems.
- Excellent customer-facing communication and listening skills with expertise in architecting solutions.
**About the job
The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. 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.
As a Cloud AI Engineer, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI. You will work with customers to identify opportunities to apply machine learning in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. Additionally, you will work closely with Product Management and Product Engineering to build and constantly drive excellence in our products.
In this role, you will work with key Google Cloud customers. Together with the team, you will support customer implementation of Google Cloud products through: architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more.
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
- Be a trusted technical advisor to customers and solve complex machine learning challenges.
- Coach customers on the practical challenges in machine learning systems: feature extraction and feature definition, data validation, monitoring, and management of features and models.
- Work with Customers, Partners, and Google Product teams to deliver tailored solutions into production.
- Create and deliver best practice recommendations, tutorials, blog articles, and sample code.
- Travel up to 30% in-region for meetings, technical reviews, and onsite delivery activities.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./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 alsoGoogle's EEO Policy ( ,Know your rights: workplace discrimination is illegal ( ,Belonging at Google ( , andHow we hire ( .
If you have a need that requires accommodation, please let us know by completing ourAccommodations 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.
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.
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 and If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form:
Cloud AI Engineer IV, Google Cloud (English) Share Cloud AI Engineer IV, Google Cloud (English)
_corporate_fare_ Google _place_ Buenos Aires, Argentina; Mexico City, CDMX, Mexico
**Mid
Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.
Share Cloud AI Engineer IV, Google Cloud (English)
_info_outline_
X
Only applications of candidates with Mexican citizenship will be evaluated for this role in compliance with the provisions of Article 7 of the Federal Labor Law.
In most instances, this position requires in-person interviews as part of the hiring process.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: **Buenos Aires, Argentina; Mexico City, CDMX, Mexico** .
**Minimum qualifications:
- Bachelor's degree in Computer Science or equivalent practical experience.
- 3 years of experience building machine learning solutions and working with technical customers.
- Experience designing cloud enterprise solutions and supporting customer projects to completion.
- Experience building and deploying custom ML models into production, including experience with deep learning frameworks and with designing and deploying agentic AI workflows for business process automation.
- Experience coding in Python, including data structures, algorithms, and software design.
- Ability to communicate in English fluently as this is a customer-facing role.
**Preferred qualifications:
- Experience working with recommendation engines, data pipelines, or distributed machine learning.
- Experience with deep learning frameworks (e.g., TensorFlow, PyTorch, XGBoost).
- Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume).
- Understanding of the auxiliary practical concerns in production machine learning systems.
**About the job
The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. 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.
As a Cloud AI Engineer, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI. You will work with customers to identify opportunities to apply machine learning in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. Additionally, you will work closely with Product Management and Product Engineering to build and constantly drive excellence in our products.
In this role, you will work with key Google Cloud customers. Together with the team, you will support customer implementation of Google Cloud products through: architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more.
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
- Be a trusted technical advisor to customers and solve complex machine learning challenges.
- Coach customers on the practical challenges in machine learning systems: feature extraction and feature definition, data validation, monitoring, and management of features and models.
- Work with Customers, Partners, and Google Product teams to deliver tailored solutions into production.
- Create and deliver best practice recommendations, tutorials, blog articles, and sample code.
- Travel up to 30% in-region for meetings, technical reviews, and onsite delivery activities.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./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 alsoGoogle's EEO Policy ( ,Know your rights: workplace discrimination is illegal ( ,Belonging at Google ( , andHow we hire ( .
If you have a need that requires accommodation, please let us know by completing ourAccommodations 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.
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.
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 and If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form:
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