Key Responsibilities:

• • Develop and implement AI agents for billing and credit recovery journeys.
  • Design solutions using Generative AI models within the Google ecosystem, including Gemini and Vertex AI.
  • Collaborate with business areas to understand needs, define hypotheses, and build result-oriented solutions.
  • Develop components and integrations using Java.
  • Create and maintain test datasets for functional, technical, and behavioral validation of AI agents.
  • Define evaluation and monitoring strategies for models and intelligent agents.
  • Build dashboards and indicators for observability, monitoring, and performance analysis using Datadog.
  • Conduct data analysis to generate insights and identify opportunities for continuous improvement.
  • Track business metrics and customer experience, proposing data-driven actions.
  • Ensure governance, traceability, and quality of implemented solutions.

Required Qualifications:

• • Bachelor's degree in Computer Science, Engineering, Statistics, Mathematics, Information Systems, or related fields.
  • Experience in Data Science, Machine Learning, or Artificial Intelligence projects.
  • Practical experience with Generative AI and Large Language Models (LLMs).
  • Knowledge of Google Vertex AI and Gemini.
  • Experience with Java development.
  • Experience in building test pipelines and validating AI solutions.
  • Knowledge in exploratory data analysis, statistical modeling, and performance metrics.
  • Experience in building dashboards and application monitoring.
  • Ability to interact with business areas and translate requirements into analytical and technological solutions.
  • Knowledge of MLOps practices, observability, and model monitoring.

Differentiators:

• • Experience in the banking, financial, or fintech sectors.
  • Background in billing, credit recovery, customer relationship, or digital channels areas.
  • Knowledge of Datadog for application observability and AI agent monitoring.
  • Experience with autonomous agent frameworks and multi-agent architectures.
  • Knowledge of Prompt Engineering, RAG (Retrieval-Augmented Generation), and LLM evaluation.
  • Experience with cloud environments and production AI solution architectures.
  • Knowledge of customer experience (CX) metrics and digital journeys.

Behavioral Competencies:

• • Strong results orientation and value generation for the business.
  • Analytical ability and critical thinking.
  • Excellent communication with technical and non-technical areas.
  • Collaborative profile and adaptable to agile environments.
  • Proactivity and sense of ownership.

Curiosity and interest in innovation and new AI technologies.