Data Scientist

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Create and deploy agentic AI solutions utilizing agent-based architectures, multi-agent systems, and cutting-edge language models.

• Design autonomous agents that can:

• - Plan and carry out intricate tasks;

• - Utilize external tools (tool calling);

• - Consume APIs and integrate with various enterprise systems;

• - Make decisions based on context and established objectives.

• Develop intelligent assistants and specialized agents for:

• - Implementing various RAG (Retrieval-Augmented Generation) strategies;

• - Automating processes;

• - Providing decision support;

• - Generating insights and content;

• - Facilitating conversational interactions and customer-facing experiences.

• Design and execute advanced GenAI pipelines including:

• - Various RAG (Retrieval-Augmented Generation) strategies;

• - Integration with both structured and unstructured knowledge bases;

• - Contextual memory strategies and management of historical data;

• - Utilization of vector databases and knowledge graphs.

• Utilize contemporary frameworks for developing intelligent agents such as:

• - LangChain;

• - LangGraph;

• - CrewAI;

• - AutoGen;

• - Semantic Kernel;

• - Other emerging frameworks.

• Develop and apply LLMOps/AgentOps practices, which include:

• - Monitoring;

• - Evaluation;

• - Observability;

• - Version control;

• - Traceability;

• - Governance of models and agents.

• Prototype Python applications that integrate with AI services, automation, and cloud ecosystems.

• Investigate and assess new architectures, techniques, and trends related to agentic AI and multimodal models.

• Collaborate with data scientists, data engineers, developers, and stakeholders within multidisciplinary teams.

• Document solutions, patterns, and insights, contributing to the team's technical advancement.

⛳️ Requirements

• Practical experience in projects involving Generative AI and Language Models (LLMs) (e.g., GPT, Claude, Llama, Gemini, etc.).

• Background in developing intelligent agents or multi-agent systems.

• Proficient in Python.

• Experience with:

• - RAG;

• - Prompt engineering;

• - Tool calling;

• - Contextual memory;

• - Management of conversational context.

• Familiarity with agent and orchestration frameworks:

• - LangChain;

• - LangGraph;

• - CrewAI;

• - AutoGen;

• - Semantic Kernel (or similar).

• Experience integrating with AI APIs and services such as:

• - OpenAI;

• - AWS Bedrock;

• - Vertex AI;

• - Azure AI;

• - Hugging Face.

• Strong foundation in:

• - Machine Learning;

• - Deep Learning;

• - NLP;

• - Recommender systems and information retrieval.

• Experience with LLMOps/AgentOps practices and production deployments.

• Nice to have:

• - Familiarity with cloud environments (AWS, Azure, or GCP);

• - Knowledge of platforms like Databricks, Snowflake, and modern data architectures;

• - Experience with vector databases:

• - Pinecone;

• - Chroma;

• - Weaviate;

• - FAISS;

• - OpenSearch;

• - Understanding of knowledge graphs and graph-based modeling;

• - Experience in building scalable applications and distributed architectures;

• - Experience working within innovation teams and emerging technology projects;

• - Intermediate/advanced proficiency in Spanish.

🏝️ Benefits

• Health insurance that covers legal dependents.

• Meal and grocery allowance (Flash Benefícios).

• Access to a telemedicine platform.

• Dental plan.

• Partnership with gyms (TotalPass).

• Pharmacy discount program.

• Life insurance.

• Private pension plan.

• Childcare assistance.

• Inclusion assistance.

• Home office allowance.

• Certification program.

• Language program.

• Educational partnerships.

• Day off for birthdays.

• Extended paternity and maternity leave.