Mid-Level AI Analyst

Accountabilities •

Evaluate AI technologies and solutions: Assess artificial intelligence tools, including generative AI, based on technical feasibility, implementation costs, potential risks, and alignment with business objectives.

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Develop and document proofs of concept: Support the planning, execution, and documentation of AI proofs of concept (POCs), helping define success criteria, test hypotheses, and evaluate results.

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Support production implementation: Collaborate with technical teams to transition AI solutions from experimental environments into production, contributing to integration design, technical requirements gathering, and solution documentation.

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Promote responsible AI practices: Apply security, privacy, compliance, and responsible-use principles, considering applicable regulations such as Brazil's General Data Protection Law (LGPD) and internal organizational guidelines.

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Establish best practices and documentation: Contribute to the development of guidelines, technical documentation, and shared learnings related to AI development, implementation, and adoption.

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Collaborate across departments: Work closely with Technology, Information Security, Legal, Data, and Business teams to identify opportunities and facilitate the implementation of AI initiatives.

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Monitor and optimize AI solutions: Track the performance and outcomes of implemented solutions, identify areas for improvement, and recommend adjustments to enhance reliability, efficiency, and business impact.

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Support AI integration and architecture: Contribute to the evaluation of system architectures and API integrations to ensure AI solutions can operate effectively within existing technology environments.

Requirements:

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Educational background: Bachelor's degree in Computer Science, Engineering, Statistics, Information Systems, or a related field.

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Cloud computing experience: Practical experience with cloud platforms, particularly Amazon Web Services (AWS).

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AI implementation experience: Hands-on experience evaluating, testing, or implementing artificial intelligence solutions.

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Knowledge of AI technologies: Practical knowledge or experience with machine learning, large language models (LLMs), and generative AI applications.

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Proof-of-concept development: Experience participating in the planning, execution, testing, and evaluation of AI proofs of concept.

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Production deployment knowledge: Understanding of the processes and technical considerations involved in moving AI solutions from experimental stages into production environments.

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Systems architecture and integrations: Knowledge of system architecture and application integration through APIs.

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Data engineering fundamentals: Basic to intermediate knowledge of data engineering concepts and practices.

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AI governance and security: Familiarity with AI governance, information security, data privacy, and regulatory requirements, including LGPD.

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Analytical and problem-solving skills: Ability to assess technical alternatives, evaluate results, identify risks, and translate business needs into practical AI solutions.

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Communication and collaboration: Strong interpersonal skills and the ability to work effectively with technical and non-technical stakeholders across different departments.

Preferred qualifications:

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Postgraduate studies, specializations, or certifications in Artificial Intelligence, Data Science, or Cloud Computing.

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Familiarity with MLOps tools, model deployment pipelines, and practices for managing AI solutions throughout their lifecycle.

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Knowledge of prompt engineering and generative AI techniques, including Retrieval-Augmented Generation (RAG) and fine-tuning.

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Experience monitoring, evaluating, and optimizing AI solution performance.

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Familiarity with responsible AI frameworks, governance standards, and security best practices.

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Advanced English proficiency.

Benefits:

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Health and dental coverage: Access to healthcare benefits designed to support your physical well-being.

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Meal and food allowances: Financial support for everyday meal and grocery expenses.

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Childcare assistance: Support to help employees manage childcare costs.

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Extended parental leave: Extended paternity leave to support family life and caregiving responsibilities.

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Health and wellness partnerships: Access to gym networks and wellness professionals through programs such as Wellhub (Gympass) and TotalPass.

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Profit sharing: Participation in profit-sharing and results-based compensation programs (PLR), subject to applicable eligibility criteria.

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Life insurance: Coverage designed to provide additional financial protection.

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Continuous learning: Access to a dedicated learning platform, university-style training resources, and partnerships with online education providers.

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Language development: Access to language-learning platforms to support professional growth and communication skills.

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Employee discounts: Access to a discount club offering savings on selected products and services.

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Physical and mental well-being: Free online resources dedicated to physical health, mental wellness, and overall quality of life.

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Family support and education: Access to pregnancy and responsible-parenting courses.

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Inclusive and accessible workplace: Support from dedicated health and well-being teams, inclusion specialists, and employee affinity groups throughout the recruitment and employment journey.

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Remote work: A remote position based in Brazil, offering the flexibility to work outside a traditional office environment. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1