Senior Ai Platform Engineer

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

Resumo da oferta

A Emagine contrata um Senior AI Platform Engineer para liderar a criação da unidade Engineering Intelligence dentro do time DevEx. Você projetará a arquitetura base de fluxos de trabalho AI-native, definindo primitivas, agentes e comandos que revolucionam a interação dos engenheiros com o código.

Você equilibrará construção técnica com um modelo de influência sobre ownership, usando métricas de engenharia para estabelecer novos padrões de P&D.

Qualificações

• 5+ anos de experiência em engenharia de software (Backend, DevOps ou Platform) com histórico de ferramentas escaláveis para outros developers.
• 2+ anos de experiência prática em espaço AI/Agentic, com foco em orquestração de LLM e integração em fluxos de trabalho de developers.
• Profundo entendimento de MCP, arquitetura de plugins e desenho de Skills, Agents e Commands para developers.
• Pensamento sistêmico sobre o ciclo de vida do developer e automação de processos manuais.
• Capacidade de comunicação estratégica para influenciar roadmaps por meio de dados.

Responsabilidades

• Arquitetar e implementar workflows AI-native complexos e multi-agente.
• Definir abstrações de workflow para automatizar o ciclo de vida do R&D.
• Integrar com o MCP para conectar ferramentas internas de task management, version control e documentação.
• Liderar o marketplace interno/framework e CLI multi-target de desenvolvimento.
• Gerar telemetria e sinais (DORA/SPACE) para acompanhar a saúde da engenharia e custo de inação.
• Conduzir PoCs e atuar como consultor para equipes de R&D para adoção de fluxos AI-native.
• Otimizar o inner loop de desenvolvimento para maior velocidade e precisão.

Conhecimentos

Software engineering

AI/Agentic

MCP & plugins

Dev lifecycle automation

Technical communication

Ferramentas

MCP

CLI tooling

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

Agentic Orchestration & Design

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.

Workflow Abstractions

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).

Ecosystem Integration

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.

Internal Marketplace & Tooling

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.

Technical Advocacy

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.

AI-Native Inner Loop Optimization

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.