Data Scientist

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Dedalus

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤖 Artificial Intelligence

Cloud • Data • Artificial Intelligence

Dedalus is a leading cloud computing company in Latin America, recognized for its expertise in cloud services and data management. They offer managed cloud services, professional cloud solutions, and data-driven AI services, partnering with major platforms like AWS, Azure, and Oracle. With a highly skilled team and a commitment to digital transformation, Dedalus aims to help businesses optimize their cloud environments and leverage innovative technologies for growth.

📋 Description

• Develop and implement agentic AI solutions using agent-based architectures, multi-agent systems, and advanced language models. • Design autonomous agents capable of: • - Planning and executing complex tasks; • - Using external tools (tool calling); • - Consuming APIs and integrating with various enterprise systems; • - Making decisions based on context and defined objectives. • Build intelligent assistants and specialized agents for: • - Implementing different RAG (Retrieval-Augmented Generation) strategies; • - Process automation; • - Decision support; • - Generating insights and content; • - Conversational interaction and customer-facing experiences. • Design and implement advanced GenAI pipelines including: • - Different RAG (Retrieval-Augmented Generation) strategies; • - Integration with structured and unstructured knowledge bases; • - Contextual memory strategies and history management; • - Use of vector databases and knowledge graphs. • Work with modern frameworks for developing intelligent agents such as: • - LangChain; • - LangGraph; • - CrewAI; • - AutoGen; • - Semantic Kernel; • - Other emerging frameworks. • Develop and implement LLMOps/AgentOps practices, including: • - Monitoring; • - Evaluation; • - Observability; • - Versioning; • - Traceability; • - Governance of models and agents. • Prototype Python applications integrated with AI services, automations, and cloud ecosystems. • Research and explore new architectures, techniques, and trends related to agentic AI and multimodal models. • Collaborate with data scientists, data engineers, developers, and stakeholders in multidisciplinary squads. • Document solutions, patterns, and learnings, contributing to the team’s technical evolution.

🎯 Requirements

• Hands-on experience in projects using Generative AI and Language Models (LLMs) (e.g., GPT, Claude, Llama, Gemini, among others). • Experience developing intelligent agents or multi-agent systems. • Advanced knowledge of Python. • Experience with: • - RAG; • - Prompt engineering; • - Tool calling; • - Contextual memory; • - Conversational context management. • Experience with agent and orchestration frameworks: • - LangChain; • - LangGraph; • - CrewAI; • - AutoGen; • - Semantic Kernel (or similar). • Experience integrating with AI APIs and services: • - OpenAI; • - AWS Bedrock; • - Vertex AI; • - Azure AI; • - Hugging Face. • Solid knowledge of: • - Machine Learning; • - Deep Learning; • - NLP; • - Recommender systems and information retrieval. • Experience with LLMOps/AgentOps practices and production deployments. • Nice to have: • - Experience with cloud environments (AWS, Azure, or GCP); • - Knowledge of platforms such as Databricks, Snowflake and modern data architectures; • - Experience with vector databases: • - Pinecone; • - Chroma; • - Weaviate; • - FAISS; • - OpenSearch; • - Knowledge of knowledge graphs and graph-based modeling; • - Experience building scalable applications and distributed architectures; • - Experience working in innovation squads and emerging technology projects; • - Intermediate/advanced Spanish.

🏖️ Benefits

• Health insurance with coverage for legal dependents • Meal and grocery allowance (Flash Benefícios) • Telemedicine platform • Dental plan • Gym partnership (TotalPass) • Pharmacy discount program • Life insurance • Private pension plan • Childcare assistance • Inclusion assistance • Home office allowance • Certification program • Language program • Educational partnerships • Birthday day off • Extended paternity and maternity leave