Principal Engineer, AI

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

📋 Description

• Oversee the technical strategy for Generative AI initiatives and intelligent solutions.

• Create architectural designs for applications utilizing LLMs, RAG, and AI agents.

• Build Java applications that integrate with AI and Machine Learning services.

• Work in collaboration with Architecture, Product, Data, and Engineering teams to enhance solutions.

• Assess new technologies, frameworks, and AI models.

• Establish development standards for applications based on AI.

• Guarantee the security, governance, scalability, and observability of intelligent solutions.

• Offer technical assistance to fellow engineers integrating AI into products.

• Develop proofs of concept (POCs) for emerging AI functionalities.

⛳️ Requirements

• Background in Software Engineering.

• Extensive experience with Java 17 and above.

• Proficiency in Spring Boot.

• Familiarity with Microservices architecture.

• Experience with REST APIs.

• Knowledge of GraphQL.

• Experience in automated testing using JUnit and Mockito.

• Understanding of Design Patterns.

• Solid grasp of SOLID principles.

• Knowledge of Clean Architecture.

• Experience with Domain-Driven Design (DDD).

• Familiarity with Event-Driven Architecture.

• Experience with CI/CD tools such as Jenkins and GitHub Actions.

• Proficiency with Docker.

• Experience with Kubernetes.

• Practical knowledge of Generative AI.

• Familiarity with Large Language Models (LLMs).

• Skills in Prompt Engineering.

• Understanding of Retrieval-Augmented Generation (RAG).

• Experience with AI Agents.

• Knowledge of Model Context Protocol (MCP).

• Familiarity with OpenAI API, Azure OpenAI, or Amazon Bedrock.

• Experience with LangChain, LangGraph, or similar frameworks.

• Knowledge of embeddings and vector databases (Pinecone, OpenSearch, pgvector, Weaviate, ChromaDB).

• Skills in fine-tuning and model evaluation (where applicable).

• Understanding of Responsible AI, governance, and AI security.

• Knowledge of model evaluation, metrics, and cost/performance optimization.

🏝️ Benefits

• Health coverage.

• Wellness programs.

• Flexible working hours.

• Opportunities for professional development.

• Remote work options.