Ai Machine Learning Engineer - Remote - Latin America
Fullstack
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Benefits offered by this job
Job summary
Pearster is hiring a Senior AI Engineer to design, build, and deploy AI-powered solutions in a fully remote setting. You will work on Generative AI, LLMs, and intelligent automation, collaborating across Engineering, Product, and business units to deliver production-ready AI systems.
This role emphasizes rapid prototyping, PoCs, and responsible AI practices, with a focus on security, scalability, and cost optimization. Strong English communication is required for international collaboration.
Qualifications
- Bachelor's in CS/Software Engineering/related STEM.
- 5+ years software development experience.
- Strong React, API development, and CI/CD.
- Experience building AI-assisted apps, agentic workflows, or tool-calling solutions.
- Experience with auth/RBAC and secure coding practices.
Responsibilities
- Architect and develop secure enterprise applications (React, TypeScript, Python, API services).
- Build agentic workflows and MCP-based integrations connecting AI applications to enterprise data/tools.
- Implement structured outputs, workflow state management, human-approval steps, and error recovery.
- Build authentication, authorization, RBAC, and audit logging.
- Implement AI evaluation, guardrails, tracing, and monitoring (quality/safety/performance/cost).
- Partner with domain experts and PMs to translate requirements into scalable solutions.
Skills
Education
Tools
Job description
Spoiler: This is where your next big move begins.
At Pearster, we are hiring an AI Engineer to join our team. This is a 100% remote position where you will be responsible for designing, building, and implementing AI-powered solutions that solve real business challenges and create meaningful impact.
You will work with modern Artificial Intelligence technologies, including Generative AI, Large Language Models (LLMs), Machine Learning, and intelligent automation, collaborating with cross-functional teams to transform ideas and business needs into scalable, production-ready solutions.
We are looking for a curious, hands‑on, and innovative professional who enjoys experimenting with emerging technologies, solving complex problems, and turning the latest advances in AI into practical solutions.
Build solutions leveraging Generative AI, Large Language Models (LLMs), and Machine Learning.
Design, develop, and deploy AI-powered applications and solutions.
Develop and integrate AI agents, APIs, and intelligent automation workflows.
Build solutions using RAG (Retrieval-Augmented Generation), embeddings, vector databases, and prompt engineering.
Integrate AI models and services from platforms such as OpenAI, Anthropic, Google, AWS, Azure, or similar providers.
Develop prototypes and Proofs of Concept (POCs) and help transform successful experiments into production‑ready solutions.
Evaluate and optimize AI solutions for accuracy, reliability, performance, scalability, and cost.
Collaborate with Engineering, Product, and business stakeholders to identify opportunities where AI can create meaningful value.
Integrate AI capabilities into existing applications, platforms, and workflows.
Contribute to responsible AI practices, including security, privacy, monitoring, and appropriate use of AI systems.
Stay up to date with emerging AI technologies, frameworks, tools, and industry best practices.
Share knowledge and contribute to building AI capabilities and best practices across the organization.
Strong programming skills, preferably in Python.
Professional experience in Software Engineering, Artificial Intelligence, Machine Learning, Data Science, or a related technical field.
Hands‑on experience building applications using Generative AI and Large Language Models (LLMs).
Experience integrating APIs and developing backend services.
Knowledge of prompt engineering, RAG, embeddings, vector databases, and AI agents.
Familiarity with AI frameworks and tools such as LangChain, LlamaIndex, Hugging Face, or similar technologies.
Experience working with AI APIs and platforms such as OpenAI, Anthropic, Google Gemini, or similar.
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
Understanding of Git, APIs, CI/CD, and modern software development practices.
Strong analytical and problem‑solving skills.
Ability to work independently in a fully remote environment.
Strong communication and collaboration skills.
Intermediate to advanced English level to collaborate effectively in an international environment.
We’re here to amplify your brilliance, not contain it.
- Work from anywhere with true flexibility and freedom.
- Earn in USD with compensation that matches your expertise.
- Recharge confidently with dedicated paid time off.
- Advance your career with fully covered international certifications.
- Access coworking spaces worldwide whenever you want a professional setup.
- Strengthen your English and expand your global reach.
- Connect and have fun with activities that unite our international team.
- Feel appreciated with personalized gifts and a thoughtful welcome kit.
- Grow our community and earn through our referral program.
At Pearster, your journey matters, and we’re here to help you go further than you imagined.
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 a Senior Agentic AI Engineer to build secure enterprise applications and agentic workflows that connect AI agents to enterprise data and tools.
- Bachelor's in CS/Software Engineering/related STEM (or Bachelor's + Master's/higher in STEM)
- 5+ years software development experience (or equivalent demonstrated skill)
- Strong React, API development, application architecture, automated testing, CI/CD
- Experience building AI‑assisted apps, agentic workflows, or tool‑calling solutions
- Experience with MCP, structured outputs, context management, or comparable frameworks
- Experience with auth/authz, RBAC, and secure coding practices
- Databricks, Unity Catalog, Data Lake, or comparable
- GitLab CI/CD or comparable
- Policy‑as‑code, infrastructure‑as‑code, configuration‑driven platforms
- Experience building data marketplaces, governance platforms, or internal developer platforms
- Familiarity with privacy/security/regulatory/AI governance controls
- Experience in regulated or risk‑sensitive environments.
- Architect and develop secure enterprise applications (React, TypeScript, Python, API services)
- Build agentic workflows and MCP‑based integrations connecting AI applications to enterprise data/tools
- Implement structured outputs, workflow state management, human‑approval steps, and error recovery
- Build authentication, authorization, RBAC, and audit logging
- Implement AI evaluation, guardrails, tracing, and monitoring (quality/safety/performance/cost)
- Partner with domain experts and PMs to translate requirements into scalable solutions
- Design reusable, configuration‑driven components for cross‑team use
- Own production‑quality code, tests, and documentation
- Mentor other engineers; guide technical direction across teams
- 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.
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.
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 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 with data structures, algorithms, and software design.
- Experience coding in Python.
- Ability to communicate in English fluently to collaborate with other teams.
Preferred qualifications:
- Experience with recommendation engines, data pipelines, distributed machine learning, and deep learning frameworks.
- Experience with 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 ( .
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.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited 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 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:
Senior Cloud AI Engineer, Google Cloud (English)
Share Senior Cloud AI Engineer, Google Cloud (English)
_corporate_fare_ Google _place_ Mexico City, CDMX, Mexico; Buenos Aires, Argentina
**Mid**
Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.
Share Senior Cloud AI Engineer, Google Cloud (English)
_info_outline_
XPlease submit your resume in English - we can only consider applications submitted in this language.
for Mexican applicants:
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: Mexico City, CDMX, Mexico; Buenos Aires, Argentina.
Minimum qualifications:
- Bachelor's degree in Computer Science, related field, or equivalent practical experience.
- 6 years of experience in software engineering, cloud architecture, or technical consulting, including 2 years of experience deploying production Generative AI (GenAI) applications.
- Experience in Python and cloud computing principles (serverless, virtualization, secure networking).
- Experience building and orchestrating agents using Agent Development Kits (ADKs) or frameworks (LangChain, LlamaIndex, AutoGen).
- Ability to communicate in English fluently to communicate with global teams.
Preferred qualifications:
- Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or related field.
- Relevant Google Cloud certifications, such as Professional Cloud Architect or Professional Machine Learning Engineer.
- Experience deploying enterprise GenAI platforms (Gemini Enterprise), with deep understanding of AI security, governance, and compliance standards.
- Experience leveraging Large Language Model (LLMs) to deploy enterprise‑scale multimodal solutions across text, image, video, and audio.
- Advanced experience implementing scalable RAG architectures connected to external productivity tools and enterprise databases.
- Proven track record leading technical project deployments and engineering teams on large cloud transformations.
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 Cloud technologies. As part of the team you will help shape the future of businesses of all sizes.
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