Sobre

• This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Engenheiro de IA Generativa Sênior based in Brazil.
• This is a senior, hands-on opportunity to build advanced AI solutions that transform how risks, controls, and complex information are analyzed across a large organization. You will lead the development of Generative AI agents, predictive models, analytical solutions, and intelligent data pipelines from technical discovery through production deployment. The role combines Generative AI, multi-agent architectures, Machine Learning, data engineering, and cloud technologies in a highly innovative environment. You will work with technologies such as LangChain, LangGraph, CrewAI, RAG, Vertex AI, Kubernetes, BigQuery, and modern MLOps and GenAIOps practices. Your work will have a direct impact on improving risk monitoring, anomaly detection, fraud identification, and decision-making through data-driven insights. This position is ideal for an experienced AI professional who enjoys solving complex problems, experimenting with emerging technologies, and building reliable AI systems at enterprise scale.
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Accountabilities

• Lead the technical discovery of AI initiatives, translating business and audit requirements into clearly defined scopes while assessing technical feasibility before architecture and development.
• Design and implement advanced Generative AI systems using multi-agent architectures, coordination frameworks such as LangChain, LangGraph, and CrewAI, and sophisticated RAG solutions for document and regulatory analysis.
• Establish and apply MLOps and GenAIOps practices covering model monitoring, experiment versioning, token and cost tracking, automated deployments, and CI/CD pipelines.
• Design, build, test, and maintain data processing pipelines capable of handling large-scale datasets from sources such as BigQuery, integrating multiple data sources using Python, Pandas, PySpark, and advanced SQL.
• Develop and optimize real-time statistical and analytical indicators, applying Machine Learning algorithms to identify anomalies, operational deviations, fraud patterns, and other relevant risks.
• Build real-time monitoring dashboards using Grafana or equivalent observability tools to help teams continuously assess risks and communicate relevant findings to leadership and committees.
• Act as an ethical and technical guardian for AI solutions by conducting bias, hallucination, jailbreak, prompt-security, and other safety tests while maintaining the confidentiality and integrity of investigative information.
• Requirements
• Solid professional experience as a Data Scientist, Machine Learning Engineer, Senior AI Engineer, or in a comparable senior technical AI role.
• Advanced Python expertise, with a strong focus on AI software engineering, application development, and API development using technologies such as FastAPI.
• Hands-on experience developing LLM-powered applications with frameworks such as LangChain, LangGraph, or CrewAI, ideally integrated with GenAIOps workflows.
• Deep knowledge of Retrieval-Augmented Generation (RAG), vector databases, and advanced prompt engineering techniques focused on improving accuracy and mitigating hallucinations.
• Strong knowledge of the Google Cloud ecosystem, particularly Kubernetes/GKE, Vertex AI, Agent Builder, Model Registry, and Cloud Run.
• Experience with agent persistence and memory solutions, including document-oriented databases such as Firestore or Datastore.
• Advanced SQL skills for extracting, cleaning, transforming, and aggregating transactional data in BigQuery.
• Practical experience with Git, automated testing, software engineering best practices, and CI/CD pipelines.
• Strong curiosity and proactivity, with a demonstrated interest in continuously testing, evaluating, and adopting emerging AI technologies.
• Excellent analytical skills, strong attention to data quality, and a rigorous approach to statistical accuracy and model performance.
• Ability to work effectively within agile teams and translate complex technical findings into clear, actionable business insights.
• Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
• Experience in financial services or Governance, Risk, and Compliance (GRC) environments is considered a plus.
• Familiarity with MLOps and GenAIOps tools such as MLflow or Vertex Pipelines is a strong advantage.
• Experience with real-time observability technologies such as Grafana, Prometheus, and OpenTelemetry is desirable.
• Google Cloud Professional Machine Learning Engineer or Professional Data Engineer certification is a plus.
• Benefits
• Opportunity to work with advanced Generative AI, Machine Learning, multi-agent architectures, and cloud technologies.
• Exposure to enterprise-scale AI initiatives with direct impact on risk monitoring, analytics, automation, and decision-making.
• Opportunity to work with modern technologies including Google Cloud, Vertex AI, Kubernetes, BigQuery, RAG, and GenAIOps.
• Highly collaborative, agile, digital, and technology-driven working environment.
• Opportunity to experiment with emerging AI technologies and contribute to innovative solutions at organizational scale.
• Inclusive environment that values diversity, innovation, collaboration, and continuous professional development.
• Additional salary, healthcare, leave, and employee benefits may be provided according to the partner company’s applicable policies.

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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.
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