Expleo

Full Stack Engineer (AI Products)

Job Locations
PT-13-Porto
Job area
IT & Digital
Employment type
Permanent
Workplace
Hybrid

Overview

Expleo is a trusted partner for your innovation journey. As a global engineering, technology and consulting service provider, we are ideally positioned to help you achieve your ambitions and future-proof your business. With a smart blend of bold thinking and reliable execution, we’re able to fast-track innovation through each step of your value chain.

We are strategically positioned to build value, with a global footprint across 30 countries.
We are as global and local as you need us to be, with strong best-in-class pan-European technological centres and unique best-shoring capabilities.

We leverage a network of high value-adding affiliates in consulting and industrial excellence, and leading partners across multiple sectors to provide you with the most comprehensive services and solutions in an ever-changing environment.

Responsibilities

- Productize a reference architecture for agents – a scalable and easily instantiated foundation for different business use cases, ensuring flexibility and alignment with specific needs;

- Integrate tools into the reference architecture that expand the range of possible agentic solutions;

- Develop both customer-facing interfaces to deliver agent recommendations to end users and backoffice interfaces to control agent behavior;

- Closely collaborate with AI Engineers, Data Scientists, and Data Architects to design, implement, and scale solutions that deliver recommendations based on AI models;

- Ensure robustness, scalability, and continuous monitoring of the developed solutions by following best practices in testing, debugging, and observability.

Essential skills

- Minimum of 3 years of experience in web application development.
- Familiarity with frontend and backend development (Django/FastAPI + React, Ruby on Rails, Flask + Vue.js);
- Ability to design scalable, modular, and reusable solutions based on microservices architecture (K8s, Docker);
- Experience with CI/CD pipelines;
- Familiarity with cloud services (Azure);
- Experience with AI-based prediction or recommendation tools is a plus;
- Experience in developing agent architectures/pipelines (valued)
- Experience in producing pipelines that automate the lifecycle of AI models using current MLOps paradigms (valued);
- Good knowledge of English.

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