Senior Staff AI-Driven Systems Architect

Amon; Lisboa; Híbrido; EUR 90 000 - 120 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Purpose-Driven Work

Leading-Edge Tech

Growth & Culture

Flexibility

Resumo da oferta

Enhesa is seeking a Staff Software Engineer in Lisbon, Portugal, to bridge the gap between architecture and rapid AI-driven delivery. You will own microservices and APIs end-to-end, lead software quality standards, and mentor engineers in a 100-person organization.

Lead AI-enabled development by leveraging Copilot, Claude Code, and Cursor, and drive integration of LLM capabilities like RAG into scalable services. A strong background in Python and compiled languages is essential.

Qualificações

• Bachelor’s or Master’s degree in Computer Science.
• 10+ years of software engineering experience.
• Strong Python skills and experience with a compiled language (C#/.NET, Go, or Rust).
• Experience with RESTful APIs, gRPC, and event-driven patterns.

Responsabilidades

• End-to-End Engineering (60%): ownership of microservices and APIs from data modeling to deployment and monitoring.
• Technical Leadership (40%): set standards for code quality and repository structure; mentor engineers across ~100-person organization.
• AI-Assisted Development: benchmark using tools like Copilot, Claude Code, and Cursor to accelerate delivery.
• AI Capability Integration: lead integration of LLM features and ML architectures (RAG) into production services.

Conhecimentos

Python

RESTful APIs

gRPC

Event-driven

Formação académica

Bachelor’s or Master’s degree in Computer Science

Ferramentas

Azure AKS/Kubernetes

AWS

GCP

Descrição da oferta de emprego

Enhesa is seeking a Staff Software Engineer in Lisbon, Portugal, to bridge the gap between architecture and rapid AI-driven delivery. You will own microservices and APIs end-to-end, lead software quality standards, and mentor engineers in a 100-person organization.

Lead AI-enabled development by leveraging Copilot, Claude Code, and Cursor, and drive integration of LLM capabilities like RAG into scalable services. A strong background in Python and compiled languages is essential.