43 AI Engineer jobs in Argentina available for remote work from home. Apply for positions such as AI Engineer, AI Engineer, AI Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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You will create Reinforcement Learning Environments to test AI models on complex software engineering tasks using Model Context Protocol tools. Responsibilities include designing reproducible environments, implementing features, refactoring code, and optimizing software performance.
Design, build, and deploy advanced AI solutions using LLMs, RAG, and agentic architectures to automate workflows and process unstructured data. Collaborate with cross-functional teams to deliver production-ready AI applications across various cloud platforms.
The AI Engineer will design, develop, and deploy end-to-end AI agent solutions within the Microsoft Azure ecosystem. Responsibilities include building RAG pipelines, managing data pipelines for unstructured data, and implementing CI/CD and responsible AI controls.
You will spearhead the development of innovative AI-driven solutions and deploy scalable products leveraging LLMs to support the payment orchestration platform. Additionally, you will design and optimize prompts while collaborating with cross-functional teams to integrate AI features into existing payment workflows.
You will own features end-to-end, including scoping, backend and frontend development, and deployment. You will also participate in code reviews, technical discussions, and infrastructure management using AI-assisted workflows.
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You will design, provision, and operate scalable production infrastructure for AI platforms and web applications across Azure and OCI. This includes managing CI/CD pipelines, implementing observability, and ensuring the reliability and security of backend services.
Design, build, and operate production services that enable AI agents to interact with real-world systems like email, payments, and web browsing. Collaborate with product and engineering teams to define reliable interfaces and workflows for agent tool use.
You will build and ship end-to-end AI-enabled applications using LangChain, LangGraph, and LangSmith while managing the full stack from backend services to modern web UIs. Additionally, you will define evaluation practices to ensure quality and collaborate with stakeholders to deliver reliable, maintainable software.
Design and build AI agents to analyze Discovery logs, execution results, and failed discoveries at scale. Develop capabilities for agents to classify failures, identify root causes, and recommend corrective actions.
Design, develop, and maintain scalable web applications while integrating AI models and generative solutions. Collaborate with engineering and business teams to optimize infrastructure performance, scalability, and costs.
Design, develop, and implement scalable Generative AI solutions using Python and LLMs. Manage cloud infrastructure as code and integrate AI components into productive environments.
The Senior QA Automation Engineer will design and enforce a robust automated testing strategy for distributed systems, Python microservices, and agentic AI workflows. They will also integrate test suites into CI/CD pipelines as quality gates and perform root-cause analysis to resolve test flakiness.
The Principal AI Engineer will lead the technical design, governance, and deployment of AI/ML solutions across a global business portfolio. This includes building reusable internal tooling, establishing security standards, and mentoring engineering teams to ensure scalable production patterns.
Design and build secure infrastructure for AI-assisted development, testing, and data-access security across the platform. Manage end-to-end projects from design documentation to production deployment using a security-first mindset.
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Build and deploy full-stack applications, internal tools, and dashboards using Claude Code. Translate specifications into production-ready software and manage projects from development through iteration.
Build and deploy full-stack applications, internal tools, and dashboards using Claude Code. Translate specifications into production-ready software and manage projects from setup through iteration.
Design and build server-side APIs and support tooling to manage large-scale data operations and backups. Utilize AI-assisted development tools to accelerate implementation while ensuring security, performance, and correctness.
The Senior AI Engineer will design, build, and deliver AI-powered features by integrating large language models into production systems. They will collaborate with ML engineers to develop end-to-end solutions, optimize prompts, and ensure the scalability and reliability of AI applications.
The role involves building agent-driven pipelines for enrollment and communication, simulating student testing for curriculum improvement, and developing automated culture/community agents. Responsibilities also include creating real-time operational dashboards and implementing AI-first workflows to reduce administrative burdens for staff.
Design and deliver production-grade AI agents while managing the full Agent Development Life Cycle from pilot to deployment. Partner with large enterprises and startups to solve complex business challenges and guide the evolution of the core platform.
The AI Native Engineer will build and embed AI-powered workflows across growth marketing, creative production, CRM, and landing pages to automate processes and improve performance. They will also develop internal tools and infrastructure to reduce manual analytical work and accelerate decision-making across the growth organization.
You will design and implement multi-step reasoning pipelines for tool-augmented AI agents while integrating them with business systems. You will also own the full development lifecycle, ensuring the agents are scalable, secure, and compliant with real-world policies.
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You will take end-to-end ownership of machine learning models, ensuring their reliable deployment and performance on physical hardware. Additionally, you will design and optimize real-time AI pipelines while collaborating with cross-functional teams and clients.
Build and deploy AI-powered workflow solutions, including prompt architectures and automation flows, for non-technical business teams. Embed within functions like Finance and HR to map current workflows and implement AI leverage to improve operational efficiency.
![Software Mind is hiring for remote [VMT] Platform AI Software Engineer](/assets/2083550c-5c59-4fae-b76e-a23e4817e5f2.jpeg){kind=small}
The role focuses on strengthening core AI systems by diagnosing performance issues and improving platform reliability and observability. You will be responsible for enhancing AI agent behavior and refactoring complex code to ensure system scalability.
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