Engenheiro de IA SR

Team: IT

Location: Brazil

Commitment: Full-time

Workplace Type: remote

Accountabilities:

The Senior AI Engineer will be responsible for designing, developing, and maintaining production-ready AI solutions, ensuring scalability, reliability, and continuous improvement. The role involves collaborating closely with technical and business stakeholders to transform complex needs into effective AI-driven products.

• Build and manage production-grade generative AI agents, including multi-agent architectures, orchestration workflows, tool calling, guardrails, and human-in-the-loop processes.
• Develop machine learning models for predictive applications, covering feature engineering, validation, deployment, and production monitoring.
• Design and evolve data pipelines based on lakehouse architectures to support AI models and intelligent systems.
• Implement systematic evaluation processes for GenAI solutions, including quality metrics, performance analysis, and cost optimization.
• Translate complex healthcare-related challenges into robust, observable, secure, and sustainable AI solutions while ensuring compliance with privacy requirements.
• Take ownership of solutions throughout their lifecycle, from initial concept and architecture decisions to deployment and continuous optimization.

Requirements:

The ideal candidate has strong experience engineering AI solutions in production environments, combining software engineering expertise, machine learning knowledge, and practical experience with modern AI architectures.

• Solid professional experience with Python development in production environments.
• Proven experience building, deploying, and managing generative AI solutions using LLM APIs, beyond proof-of-concept projects.
• Strong knowledge of AI agent orchestration frameworks such as LangGraph, LangChain, CrewAI, or equivalent technologies.
• Experience with applied machine learning, including predictive modeling, validation, tuning, and deployment processes.
• Experience working with data lakehouse architectures such as Delta Lake, Iceberg, or similar technologies.
• Hands-on experience with cloud platforms, preferably Google Cloud Platform, including services such as BigQuery, Vertex AI, Cloud Run, and GCS.
• Knowledge of AI evaluation methodologies, RAG systems, LLM observability, or Model Context Protocol (MCP) is a plus.
• Experience with workflow orchestration tools such as Airflow, Kestra, Dagster, or similar is desirable.
• Previous exposure to healthcare technology, clinical data, billing systems, or healthcare interoperability is considered an advantage.
• Strong ownership mindset, pragmatic problem-solving skills, and the ability to communicate technical concepts clearly.

Benefits:

• Remote work model with flexibility and autonomy.
• Onboarding kit and equipment provided for professional activities.
• Semestral company gathering focused on culture and strategy alignment.
• Monthly allowance through Flash benefits card.
• Paid company recess period.