Staff AI Engineer

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

📋 Description

• Integrate Generative AI models, including LLMs, with external APIs, tools, and databases utilizing secure and efficient orchestration methods.

• Design, develop, and implement AI workflows and Agentic AI solutions, enabling the smooth orchestration of intelligent agents to plan and execute tasks while utilizing both autonomous and human-in-the-loop approaches.

• Implement and enhance multi-agent systems by leveraging standards and protocols such as the Model Context Protocol (MCP) and new frameworks for agent interoperability and access to external resources.

• Develop evaluation frameworks, metrics, and checkpoints for agent autonomy, performance, and safety, ensuring adherence to moderation, security, and ethical standards.

• Evaluate, analyze, and extract insights from structured and unstructured data using Generative AI models and pipelines.

• Ensure effective AI agent operations by applying observability, monitoring, and MLOps best practices, facilitating dependable deployment pipelines and ongoing performance optimization.

• Orchestrate AI model selection, tuning, and performance validation tailored to the specific needs of agent-based applications.

• Convey complex AI concepts, systems, and decisions clearly to both technical and non-technical stakeholders, fostering transparency and trust in AI delivery.

• Cultivate an innovative and collaborative environment, motivating teams to tackle complex challenges and share ideas that promote creative solutions.

⛳️ Requirements

• Demonstrated experience in designing and deploying AI architectures, with a focus on Generative AI, NLP, LLM integration, and software engineering.

• Solid background in building software platforms (Python/Django, Java/Spring, TypeScript/Express, etc.) capable of API integration and orchestration.

• Strong grasp of the trade-offs associated with various generative AI models and the capability to select the appropriate model for specific use cases.

• Practical experience with function-calling and tools integration into LLM models, utilizing frameworks like the Model Context Protocol (MCP).

• Familiarity with Agentic AI orchestration frameworks such as LangGraph, Google ADK, OpenAI Agents SDK, CrewAI, or similar.

• Proficiency in data embeddings, vector databases, and chunking strategies, with an understanding of the trade-offs between different options to optimize data ingestion and application performance.

• Experience using CI/CD tools (GitHub Actions, Jenkins, AWS CodeDeploy, Azure Pipelines) to enhance development and deployment workflows.

• Hands-on experience deploying software on major cloud platforms and utilizing AI tools such as AWS Bedrock and Azure AI Services.

• Experience with evaluation frameworks (e.g., RAGAS, OpenAI Eval) and tools (e.g., Arize, LangSmith, Braintrust) to assess business and performance metrics of AI solutions.

• Understanding of performance optimization techniques, including the use of observability platforms, event tracking, and performance validation.

• Practical knowledge of deploying AI solutions using cloud platforms like AWS, Azure, or GCP, employing services such as AWS Bedrock or Azure AI Services.

• Excellent skills in prompt and context engineering, ensuring the application of appropriate techniques to meet diverse project needs.

• Capacity to effectively communicate complex AI solutions and concepts to both technical and non-technical stakeholders.

🏝️ Benefits

• Health and dental plan

• Life insurance

• Monthly voucher for meals, culture, education, health, and mobility

• Child care assistance and more!