Engineer | DevOps AWS

Role

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

Location

: Barcelona, Spain

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.

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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