Forward Deployed Engineer, Generative AI, Google Cloud (Spanish, English)
Forward Deployed Engineer, Generative AI, Google Cloud (Spanish, English)
Role level: Mid
Location: Bogotá, Bogota, Colombia; Buenos Aires, Argentina; Santiago, Chile; Mexico City, CDMX, Mexico; Lima, Peru; "+4 more" and "+3 more".
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., Google Cloud Platform (GCP)).
Experience building pipelines for structured and unstructured data using both vector databases and RAG‐like architectures to power enterprise AI solutions.
Experience writing code for machine learning, natural language processing, and generative AI agents.
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).
Knowledge of "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.
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.
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, 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.
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 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.
Collaborate with technical sales teams to instill Google‐grade development best practices, ensuring long‐term project success and high end‐user adoption.
Equity and Benefits
Equity is granted exclusively and discretionally by Alphabet Inc.
G SU 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.
We offer a competitive salary, benefits, and a culture that fosters innovation and collaboration.
EEO Statement
Google is proud to be an equal opportunity workplace and an affirmative action employer.
We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity or veteran status.
We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
Google is also compliant with the U.S. Equal Employment Opportunity Commission and the Department of Labor's affirmative action regulations.
We also consider applicants regardless of disability, age, gender, or any other protected class to the extent allowed by law.
AgileEngine, Inc.
Overview
AgileEngine is an Inc. **** 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.
Why Join Us (AgileEngine)
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
About the Role (AgileEngine)
We are looking for an Agentic AI Engineer to build generative AI workflows that automate cloud configuration baselines and remediation.
Requirements & Hiring Criteria (AgileEngine)
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 interdisciplinary engineering teams.
Nice to Have (AgileEngine)
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.
What You Will Do (AgileEngine)
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.
Perks And Benefits (AgileEngine)
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.
ML / AI Engineer Senior Remoto Argentina, ID #*****
Toolkits RAG: LangChain Retrievers, LlamaIndex integrations.
Ambiente Cloud & Serverless GenAI
#J-*****-Ljbffr

📌 Remote Generative Ai Engineer (Llms & Pipelines) (Buenos Aires)
🏢 encora10
📍 Buenos Aires