Engenheiro de IA SR

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.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
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