Senior Ai Platform Engineer

Emagine; Lisboa; Presencial; EUR 90 000 - 120 000; Tempo integral

Resumo da oferta

A Emagine procura um Senior AI Platform Engineer para o time DevEx, encarregado de arquitetar fluxos de IA nativos e construir as primitivas que guiarão centenas de engenheiros no código.

Você será membro fundador da unidade de Engenharia Inteligente, conectando MCP, agentes e comandos com o objetivo de melhorar a produtividade, governança e escalabilidade do ecossistema de desenvolvimento.

Qualificações

• 5+ anos de experiência em engenharia de software (Backend, DevOps ou Platform).
• 2+ anos em AI/Agentic, com foco em orquestração de LLM e integração em fluxos de trabalho de desenvolvimento.
• Domínio de MCP (Model Context Protocol) e arquiteturas de plugins.
• Visão de Systems Thinking para automatizar processos manuais.
• Capacidade de coletar feedback, conduzir reuniões e influenciar roadmaps com credibilidade técnica.

Responsabilidades

• Arquitetar e implementar fluxos de IA nativos complexos (multi-agentes, RAG, loops de avaliação).
• Definir constructs centrais (Skills, Agents, Commands) para automatizar o ciclo de vida do desenvolvimento.
• Integrar o MCP com ferramentas internas (gestão de tarefas, versionamento e documentação).
• Conduzir evolução de marketplace interno e CLI multi-alvo com foco em segurança, governança e extensibilidade.

Conhecimentos

LLM orchestration

Agentic framework design

Developer productivity telemetry

MCP knowledge

Technical communication

Descrição da oferta de emprego

Descrição do cargo

As a Senior AI Platform Engineer in the Developer Experience (DevEx) team, you will be a founding member of a specialized unit acting as the Engineering Intelligence center for our R&D organization. Your mission is to architect the foundational architecture for AI-native workflows. You won't just be using AI; you will be building the primitives and abstractions—agentic frameworks, commands, and skills that redefine how hundreds of engineers interact with the codebase. This role balances deep technical systems building with a data-driven "influence over ownership" model, using engineering health metrics to pioneer new R&D standards.

Job Responsibilities and Expectations

• Architect and implement complex AI-native workflows, including: Multi-agent systems and orchestration. Codebase-specific RAG (Retrieval-Augmented Generation). Custom evaluation loops to ensure high-quality AI-assisted outputs.
• Define the standard "language of work" for R&D by designing core constructs for Skills, Agents, and Commands that automate and reinvent the developer lifecycle (from specification and planning to implementation).
• Leverage and integrate with the Model Context Protocol (MCP) to connect the internal toolchain—including task management, version control, and documentation—into a unified, actionable context for AI agents.
• Lead the evolution of an internal developer marketplace|framework and a multi-target CLI. You will build foundational development skills and commands while ensuring the platform remains secure, governed, and extensible for other teams. Define and produce the telemetry and signals required to track engineering health (e.G., DORA and SPACE metrics). You will use data from engineering metrics platforms to identify bottlenecks and perform "cost of inaction" analysis.
• Drive the adoption of AI-native workflows by: Leading Proof of Concepts (PoCs). Managing feedback loops with stakeholders. Acting as a consultant to other R&D teams to influence their performance and adoption.
• Lead the evolution of the developer cycle by optimizing the agentic development flow. You will: Ensure high-fidelity context availability through seamless integrations. Refine the human-AI interaction model to minimize friction. Ensure the agentic workflow is significantly faster and more accurate than manual execution.

Requirements

• Professional Background: 5+ years of software engineering experience (Backend, DevOps, or Platform) with a track record of building maintainable, scalable tools for other developers.
• AI Specialization: 2+ years of hands‑on experience in the AI/Agentic space. You must have deep context on LLM orchestration, agentic framework design, and the integration of AI into developer workflows.
• Technical Conceptual Depth: Deep understanding of MCP (Model Context Protocol), plugin architectures, and the design of developer-facing Skills, Agents, and Commands.
• Systems Thinking: A deep understanding of the developer lifecycle and the ability to translate complex manual processes into automated, agentic constructs.
• Strategic Communication: Proven ability to collect feedback, drive meetings, and influence other teams' roadmaps through technical credibility and data-driven arguments.

Ways to Stand Out

• Experience building and maintaining internal-facing developer products or CLI tools used at scale.
• A background in Platform Engineering with a heavy focus on developer productivity and telemetry.
• Active participation or contributions to the open-source AI or Agentic ecosystem.