AI Platform Engineer

hace 7 horas

Barcelona, Barcelona, España E-Solutions A tiempo completo

Role
: AI Platform Engineer (
Data, Infrastructure & Agentic Systems
)

Location
: Barcelona, Spain

6 months extendable contract

Rate: Euro 300 MAXX

Mandatory:
agentic AI

Key Responsibilities

  • Engineer robust data and cloud foundations
    to support AI workloads and automation at scale across AWS environments.
  • Design and implement agentic AI systems
    as part of a broader automation stack—developing self-orchestrating workflows, APIs, and reusable platform components.
  • Build automation and observability solutions
    using Infrastructure-as-Code (Terraform/CDK) and modern monitoring frameworks.
  • Integrate data pipelines
    with intelligent orchestration layers to enable autonomous experimentation and deployment.
  • Collaborate across disciplines
    —partnering with data engineers, AI scientists, and platform specialists to embed AI capabilities into core operations.
  • Champion responsible and scalable AI automation
    , ensuring compliance, reliability, and transparency by design.

Required Experience & Skills

  • Strong software engineering background with
    Python, TypeScript
    , or similar languages.
  • Proven experience building and automating cloud infrastructure using
    AWS
    (EC2, IAM, S3, Lambda, CloudWatch, etc.) and
    Infrastructure-as-Code
    tools (Terraform/CDK).
  • Solid understanding of
    data engineering principles
    —pipeline design, data flow orchestration, and API integration.
  • Experience with
    CI/CD pipelines
    and Git-based workflows.
  • Demonstrated experience in use of
    AI tools
    (e.g., claude, Copilot, LangChain, agent frameworks) to enhance productivity.

  • A
    self-driven, curious problem solver
    who experiments and iterates toward impactful solutions.

  • Experience deploying or integrating
    agentic AI architectures
    , such as orchestration frameworks or autonomous agents.

  • Knowledge of
    RAG pipelines
    , embeddings, and vector databases (e.g., Weaviate, Qdrant).
  • Familiarity with
    Kubernetes/EKS
    and observability tools (New Relic, OpenTelemetry).
  • Understanding of
    model hosting and optimization
    (vLLM, Triton, HuggingFace).
  • Awareness of
    data governance and responsible AI practices
    in enterprise or regulated settings.

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