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.
Requirements & QualificationsTechnical Skills & Experience
- 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 & Soft Skills
- 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.
Pagamento: 1 600,00€ - 2 500,00€ por mês
Benefícios:
- Cartão/Ticket refeição
- Seguro saúde
Localização do trabalho: Trabalho remoto híbrido em Lisboa
