Job Description

Job Description
You will be part of the development of solutions based on language models and generative AI technologies, from the definition of the architecture to its deployment, monitoring and improvement.
Responsibilities:
Design, develop and implement internal products and solutions based on artificial intelligence.
Create AI systems using technologies such as LLM, RAG, AI tools, workflows and agent-based architectures.
Manage the complete development cycle of AI solutions, including problem definition, architecture, implementation, evaluation, deployment and optimization.
Collaborate with product, engineering and business teams to integrate artificial intelligence into real processes and applications.
Design and implement evaluation and quality control frameworks for AI systems.
Develop scalable, secure and efficient inference pipelines, optimizing latency, costs and observability.
Participate in projects related to user onboarding, customer service, document and transaction classification, smart assistants, fraud detection and process automation.
Contribute to the evolution of the platform and the artificial intelligence tools used by the organization.
Propose technical improvements, participate in the definition of the technological roadmap and encourage the adoption of good practices.
Experiment with new AI technologies and methodologies to continually improve the performance and quality of the solutions developed.
Requirements:
Demonstrable experience developing and implementing artificial intelligence systems in production environments.
Proficient in Python and knowledge of software engineering.
Practical experience with LLM based applications.
Experience with technologies such as RAG, use of tools (tool calling), agent-based architectures, prompt engineering, model evaluation, generation of structured results, security mechanisms or fine-tuning.
Experience integrating artificial intelligence systems into backend applications or digital products.
Ability to design processes for evaluating, monitoring and improving AI systems.
Experience with cloud infrastructure and deployment of containerized applications.
Ability to work autonomously, assume responsibilities and function in uncertain environments.
Experience evaluating and incorporating new artificial intelligence models, tools and architectures in production environments.
Up-to-date knowledge of the AI ​​ecosystem and ability to convert technological developments into practical solutions for the business.
Fluent level of English.

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