Senior AI Engineer

RequirementsBachelor's or Master's degree in Computer Science, Software Engineering, or a related field.Minimum of 2 years of experience in Machine Learning, Generative AI, or Data Science.Strong software development experience, with solid knowledge of Python.Hands-on experience with Large Language Models (LLMs), particularly GPT, Transformers, and Hugging Face.Practical experience in AI/ML model fine-tuning and Prompt Engineering.Knowledge of LLM parameter experimentation and optimization, including temperature and top-p.Experience with AWS, particularly SageMaker and Bedrock, or equivalent Azure services.Solid understanding of databases, software architecture, and scalable system design.Knowledge of AI Governance, AI Guardrails, API security, and data privacy.Experience developing Proofs of Concept (POCs) and working with tools such as Jupyter Notebooks.Knowledge of cloud-native architectures and AI solution integration into business applications.Experience with Agile/Scrum methodologies.Fluent in English.Nice to HaveRelevant certifications in AWS, Azure, or Artificial Intelligence.Experience developing and deploying production-grade AI solutions.Knowledge of MLOps and AI Governance frameworks.Experience with C#/.NET or Java/Spring Boot.Familiarity with Docker, Kubernetes, and DevOps/CI/CD pipelines.ResponsibilitiesTranslate business requirements into functional applications and innovative AI/LLM-based solutions.Design, develop, fine-tune, deploy, and optimize Machine Learning and Artificial Intelligence models.Develop and optimize prompts for LLM-based solutions through Prompt Engineering.Experiment with and fine-tune model parameters, such as temperature and top-p, to improve model performance.Develop Proofs of Concept (POCs) for Research & Development initiatives using tools such as Jupyter Notebooks.Analyze complex datasets and identify opportunities for AI model implementation.Implement AI Governance practices, guardrails, auditing mechanisms, and secure AI usage standards.Design scalable, robust, cloud-native architectures and integrate AI solutions into business applications.Develop cross-functional services and foundational components that can be reused across different business areas.Ensure API security, data privacy, and responsible use of AI solutions.Collaborate with multidisciplinary teams to develop and enhance technological solutions.Participate in code reviews, share technical knowledge, and mentor other team members.3x por semana