Senior / Lead AI Data Infrastructure Engineer

N-iX
Barcelona, Spain
13 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Shift work
Languages
English
Experience level
Senior

Job location

Barcelona, Spain

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Amazon Web Services (AWS)
ARM
Cloud Computing
Computer Programming
Data Architecture
Data Infrastructure
Monitoring of Systems
Identity and Access Management
Python
Machine Learning
Open Source Technology
Performance Tuning
Software Engineering
Snowflake
Generative AI
Amazon Web Services (AWS)
Data Lake
Machine Learning Operations
Serverless Computing

Job description

  • Platform Ownership: Set up, maintain, and own the core AI platform infrastructure with a primary focus on Snowflake Cortex and its surrounding ecosystem.
  • Infrastructure as Code & Tooling: Configure and maintain MCP (Model Context Protocol) servers and manage the integration of open-source packages (e.g., Goose).
  • Cost & Performance Optimization: Actively manage Snowflake credits, token usage, and overall system performance to ensure a cost-effective and resilient environment.
  • Data Architecture: Modernize and refine high-level platform architecture, ensuring external datasets are seamlessly integrated and "AI-ready."
  • Observability: Implement and maintain high standards for system monitoring, observability, and reliability.
  • Technical Leadership: Act as a self-starting, independent lead who can translate high-level infrastructure needs into functional, production-grade code.

Requirements

  • Expert-level Snowflake: Extensive hands-on experience with Cortex, including setup, management, and cost optimization.
  • Snowflake Suite: Deep expertise (SME) in Snowpark and Streamlit.
  • Programming: Advanced proficiency in Python and a strong background in Software Engineering.
  • AI Infrastructure: Proven experience in MCP (Model Context Protocol) server development and configuration.
  • Cloud & Data:
  • Deep understanding of data modeling, data architecture, and AWS environments (specifically AWS Bedrock).
  • Proficiency in core AWS infrastructure: S3 (data lakes), IAM (permissions/security), Lambda (serverless compute), and VPC/Networking (secure cloud connectivity).
  • Seniority: Minimum 5+ years of experience in data/infrastructure engineering, showing the ability to work independently and interface directly with internal technical stakeholders., * GenAI/RAG: Practical experience deploying Generative AI and Retrieval-Augmented Generation (RAG) systems in a production setting.
  • Machine Learning: A background in ML engineering or MLOps (e.g., experience with AWS SageMaker).

Open Source: Experience contributing to or managing open-source AI tooling like Goose.

Benefits & conditions

  • Flexible working format - remote, office-based or flexible

  • A competitive salary and good compensation package

  • Personalized career growth

  • Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)

  • Active tech communities with regular knowledge sharing

  • Education reimbursement

  • Memorable anniversary presents

  • Corporate events and team buildings

  • Other location-specific benefits

  • not applicable for freelancers

About the company

Unlike a traditional AI Developer, your focus will be on the infrastructure, tooling, and ecosystem that powers AI, rather than building individual end-user solutions. You will modernize our data environment, making it "AI-ready," and ensure our platform is robust, scalable, and cost-optimized to support the next generation of online education and healthcare simulations. About the Client Our customer is a leader in online education, dedicated to empowering professionals through innovative simulation and learning platforms. We are a certified great workplace, ranked consistently by Fortune as a top employer for Millennials and Women. You will join the Data, AI & Automation (DAIA) team-a tight-knit, remote-first group of passionate experts driven by curiosity. We work in a fast-paced environment where we value "human-centric" AI that solves real-world problems in the healthcare and allied health fields.

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