AI Engineer

*About the Role*

We are seeking a skilled AI Engineer to drive the implementation, deployment, and optimization of artificial intelligence solutions across our product ecosystem. In this role, you will collaborate with cross\-functional teams to transform functional prototypes into robust, production\-ready AI services. The ideal candidate possesses deep backend software engineering fundamentals alongside specialized expertise in working with APIs, LLM orchestration frameworks, and vector databases.

*Key Responsibilities*

• Application Architecture \& Development: Design and build end\-to\-end, LLM\-powered applications, workflow automations, and autonomous AI agents.


• Model Integration: Connect, orchestrate, and maintain external and self\-hosted AI model APIs under real\-world runtime constraints.


• Context \& Retrieval Engineering: Develop and maintain Retrieval\-Augmented Generation (RAG) structures, advanced prompt engineering chains, and data pipelines over proprietary business data.


• System Evaluation \& Monitoring: Implement observability and evaluation tooling to continuously grade, monitor, and audit AI system performance, bias, and accuracy.


• Cross\-functional Collaboration: Work closely with engineers and frontend developers to smoothly transition proof\-of\-concepts into consumer\-ready software.


• Reliability Engineering: Address complex edge cases such as error handling, model drift, fallback mechanics, and self\-healing system pipelines.

• Software Fundamentals: Proficiency in Python (highly critical) and/or modern backend ecosystems like Node.js/TypeScript. Strong grasp of data structures, algorithms, and microservices.


• AI Toolkits: Experience with orchestration layers, model hosting platforms, and vector databases.


• Cloud \& DevOps: Familiarity with deploying applications via cloud infrastructure like AWS, Google Cloud, or Microsoft Azure.


• Data Literacy: Solid command of SQL and data manipulation libraries, alongside a foundational understanding of data science principles.

• Education: Bachelor’s degree in computer science, Data Science, Mathematics, or a related technical discipline (or equivalent practical experience).


• Communication: Ability to articulate complex technological decisions and mechanics to non\-technical stakeholders and leadership teams.


• Problem Solving: A proactive, scientific approach to troubleshooting non\-deterministic software behaviour.

Benefícios:

• Cartão/Ticket refeição


• Seguro saúde

Este anúncio é de Indeed. Ver anúncio original ↗