GCP AI Architect

GCP AI Architect

Location: Lisbon, Portugal

Main Responsibilities

• Lead, together with the Functional Architect, the design process of AI/Gen
  AI solutions, from conception to implementation.
• Define the Technical Architecture based on project requirements, selecting the ideal components (e. g. , Serverless vs. Kubernetes, Cloud SQL vs. No
  SQL, Caching, Storage).
• Ensure the application of best practices in security, cost management, governance, and compliance for AI usage in Public Cloud environments.
• Orchestrate Gen
  AI solution modules: LLMs, embeddings, vector databases, data ingestion, monitoring, and observability.
• Lead Proofs of Concept (Po
  Cs) and act as a technical reference for development teams.
• Actively contribute to reference frameworks, architecture patterns, and technical documentation.
• Work autonomously to identify and resolve complex technical problems in contexts with multiple stakeholders.

Mandatory Requirements

• Education: Bachelor’s degree in Computer Engineering or a similar field.
• Certification: At least one of the following certifications: Google Certified Professional Cloud Architect or Azure Solutions Architect Expert.
• Proven Experience: Solid experience designing solutions with Cloud-Native Architectures in Public Cloud, with a clear preference for GCP.
• Cloud Technical Knowledge:
  • Mastery of GCP technologies (Pub/Sub, Cloud Run, Cloud SQL, GKE, Cloud Storage, etc. ).
  • Deep knowledge of Cloud security and application of “security by design” principles.
  • Experience with
    - driven architectures and integration strategies.
• AI/Gen
  AI Knowledge:
  • Experience with Cloud-based LLMs (Azure Open
    AI, Vertex AI, or equivalent).
  • Practical knowledge in RAG and Vector Databases (e. g. , Mongo
    DB, Postgre
    SQL, Big
    Query Vector Search).
  • Familiarity with Gen
    AI frameworks such as Lang
    Chain, Llama
    Index, or Agent Development Kit (ADK).
• Excellent communication and leadership skills to drive architecture discussions.
• Strong autonomy and resilience in highly complex and ambiguous contexts.

Nice-to-Have

• Deep knowledge of integration technologies such as Kafka and Apigee.
• Experience with Data Mesh ecosystems.
• Knowledge of security applied to Gen
  AI (e. g. , sensitive data controls, prompt injection prevention).
• Practical experience in MLOps processes and AI model governance.

Seniority level

Mid-Senior level

Employment type

Contract

Job function

Information Technology

Industries

Staffing and Recruiting