Remote Senior Java/Kotlin Backend Engineer (Cloud-Native)

BairesDev; Quilmes; Remote; ARS 184,482,000 - 245,976,000; Full time

Job summary

BairesDev is seeking a Cloud AI Engineer specializing in Google Cloud to join our Buenos Aires/Mexico City delivery teams. You will design and implement ML solutions for customer use cases, leveraging TensorFlow, DataFlow and Vertex AI, and travel up to 30% for on-site engagements.

You will collaborate with customers, partners, and Google Product teams to deploy production-ready pipelines, perform data migrations, and share best practices through tutorials and sample code.

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.

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.

Skills

Serverless

Azure Integration

Azure Functions

Logic Apps

Event-driven

Triggers

Bindings

Function apps

Azure Functions Core Tools

iPaaS

Azure Service Bus

Event Grid

API Management

Education

Bachelor's degree in Computer Science

Tools

Azure Functions Core Tools

Azure Service Bus

Event Grid

API Management

iPaaS platforms

Job description

• Experience in Serverless Solutions and Azure Integration Deep experience building solutions with Serverless and Azure Integration , including Functions and Logic Apps for event-driven systems.
• Azure Functions Hands-on expertise in developing serverless computing solutions. Working with triggers (HTTP, Timer, Queue, Event Grid). Utilizing bindings , function apps , scaling strategies, and local development using Azure Functions Core Tools .
• Azure Logic Apps Extensive experience with iPaaS (Integration Platform as a Service). Building workflows via the visual designer . Leveraging pre-built connectors and integrating diverse applications and data sources. Managing JSON schema definitions for triggers and configuring retry policies .
• Connecting Serverless Components Strong ability to connect serverless components using Azure Service Bus (for message queuing) and Event Grid (for event routing), building resilient and decoupled architectures.
• Azure API Management Designing, publishing, and securing APIs, especially those backed by serverless backend services.

Location: Buenos Aires, Argentina; Mexico City, CDMX, Mexico

Cloud AI Engineer, Google Cloud

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.

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.

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.

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: **Buenos Aires, Argentina; Mexico City, CDMX, Mexico**.

To all recruitment agencies: Google does not accept agency resumes.

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 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 also Google's EEO Policy ( ,Know your rights: workplace discrimination is illegal ( ,Belonging at Google ( , and How we hire ( .