20 publicaciones de empleo destacadas de cost engineer en b (¡Están contratando!)

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n8n —Buenos Aires, Buenos Aires
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TELUS Digital —Buenos Aires, Buenos Aires
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Salesforce —Buenos Aires, Buenos Aires
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Philip Morris International —Buenos Aires, Buenos Aires
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TechBiz Global GmbH —Buenos Aires, Buenos Aires
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Freelance Senior DevOps Engineer
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Forward Deployed Engineer II, Generative AI, Global Service Delivery (English, Spanish)

Google -
Buenos Aires, Buenos Aires

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Detalles del empleo

Tiempo completo
Hace 17 horas

Descripción completa del empleo

In most instances, this position requires in-person interviews as part of the hiring process.

Please submit your resume in English - we can only consider applications submitted in this language.

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.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mexico City, CDMX, Mexico; Buenos Aires, Argentina.

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., Google Cloud Platform (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.
Ability to communicate in Spanish and English fluently to support client relationship management in this region.

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).
Experience leading technical discovery sessions.
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 job

As 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. 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. Your 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 leverage 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

Design, develop, test, deploy, maintain, and improve machine learning models and AI software components.
Implement and optimize ML algorithms using frameworks like TensorFlow, PyTorch, JAX, or others.
Work with large-scale datasets, leveraging Google's infrastructure for data preprocessing, feature engineering, and model training.
Collaborate closely with product managers, researchers, and other engineering teams to translate product requirements into technical solutions.

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.

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