Senior AI Engineer (FullStack)

Posted 1 day agoViewed

💎 Seniority level: Senior

📍 Location: São Paulo, Rio Grande do Sul, Rio de Janeiro, Belo Horizonte

🔍 Industry: Software Development

🪄 Skills: Backend DevelopmentDockerNode.jsPythonArtificial IntelligenceFrontend DevelopmentFull Stack DevelopmentMachine LearningReact.jsSoftware ArchitectureTypeScriptAzureData engineeringData scienceCommunication SkillsCI/CDAgile methodologiesRESTful APIsSoftware Engineering

Requirements:

Experience building and testing FullStack applications (using TypeScript/React for frontend, Python/Node.js for backend), while integrating with AI components.
Strong understanding of the trade-offs between various generative AI models and the ability to choose the right model for specific use cases.
Experience with RAG, understanding the trade-off between available architectures, including embeddings, vector databases, and design patterns.
Hands-on experience deploying software on Azure AI Services using Azure Pipelines.
Experience with performance optimization and observability platforms.
Proficiency in conducting experiment tracking and implementing complex AI integrations with minimal oversight.
Ability to communicate complex AI solutions and concepts effectively to technical and non-technical stakeholders.
Familiarity with testing and evaluating AI systems using state-of-the-art methods and best practices.
Strong collaboration skills and ability to work alongside Data Science specialists, drawing on their expertise in AI model development and fine-tuning to deliver sophisticated AI solutions.

Responsibilities:

Apply your knowledge of software engineering and AI systems to develop AI solutions that directly address and resolve business problems.
Implement end-to-end solutions by taking ownership of the Frontend, Backend, and AI stacks of the development.
Adhere to development best practices such as clean coding, unit testing, and automated deployment.
Navigate and manipulate generative AI models, including large language models, to create prompts and solutions tailored to specific use cases.
Develop and incorporate AI solutions while adhering to industry best practices, including moderation, security, and compliance standards.
Lead the charge in designing, measuring, and evaluating Agentic AI solutions, considering functional and non-functional requirements (e.g., cost, accuracy, latency).
Translate AI research into production-ready features, delivering robust and scalable AI components that integrate seamlessly with larger systems.
Drive the selection and application of appropriate evaluation metrics, ensuring that AI solutions are robust, unbiased, and meet all necessary performance standards.

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