---
title: "AI Engineer"
company: "WIZELINE"
company_url: "https://www.remjobs.works/companies/wizeline"
url: "https://www.remjobs.works/job/wizeline-ai-engineer-73464f2d-58cd-4f4f-9f82-e0d81940b649"
apply_url: "https://www.wizeline.ai/careers/job?gh_jid=8214794"
workplace: onsite
location: "Barcelona - Spain"
employment_type: unspecified
seniority: mid
role: ai-machine-learning
region: europe
skills: ["aws", "docker", "gcp", "llm", "nextjs", "nlp", "nodejs", "python", "react", "typescript", "vue"]
date_posted: 2026-09-18T21:48:16.000Z
first_seen_by_remjobs: 2026-09-18T21:56:57.984Z
---

# AI Engineer

**WIZELINE** · Barcelona - Spain

Apply: https://www.wizeline.ai/careers/job?gh_jid=8214794

## About WIZELINE

Wizeline accelerates your roadmap through nearshoring and expert AI advisory services, improving efficiency, speeding execution, and driving sustainable innovation.

## About the role

**We are:**
Wizeline, a global AI-native technology solutions provider, develops cutting-edge, AI-powered digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of growth, collaboration, and impact.

With the right people and the right ideas, there's no limit to what we can achieve.

**Are you a fit?**
Sounds awesome, right? Now, let's make sure you're a good fit for the role:

##### Key Responsibilities

- Architect and ship end-to-end agentic and LLM-powered tools for business-facing use cases, deciding when to use a single LLM call, an iterative LLM loop, or a full multi-agent system based on real task complexity.

- Design AI-agnostic, model-flexible services that allow the team to evaluate and swap the best-performing model for each task.

- Build production tools that transform raw content into structured, ready-to-use output — for example, systems that reformat content to defined templates/guidelines or consolidate multiple sources into a single, fact-accurate output without inventing information.

- Develop and maintain RAG pipelines and vector database integrations to support retrieval-driven features such as content linking and recommendations.

- Establish and scale prompt evaluation, testing, and regression-control frameworks (e.g., via Braintrust, MCP tooling, LangFuse) so quality holds as tools expand across teams and use cases.

- Take AI features from prototype/PoC through to deployed, end-user-facing production tools, working across the full stack (AI core services in Python/TypeScript, front-end integration in React/Vue/Next.js) without relying on handoffs to other teams.

- Partner with stakeholders and engineering leadership to gather feedback, measure impact (e.g., time saved, approval rates), and iterate on tools in production.

- Extend proven architectures to onboard new use cases as configuration rather than one-off rebuilds.

- Stay current on GenAI, NLP, ML, and IR technologies, incorporating best practices and cloud infrastructure to improve system efficiency.

##### Must-have Skills

- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related STEM field, or equivalent work experience.

- 4+ years of industry experience in machine learning engineering, AI engineering, or a related software engineering role.

- Strong programming skills in Python and/or TypeScript/Node.js, with the ability to build both AI core services and the interfaces that consume them.

- Hands-on experience deploying LLMs in production, building automated evaluation pipelines (e.g., LLM-as-a-judge), and architecting multi-agent systems that use tool-calling and long-term memory to solve non-linear problems.

- Practical experience with LangChain and its ecosystem (e.g., LangGraph, LangSmith) or comparable agent-orchestration frameworks.

- Experience with RAG architectures and vector databases in production settings.

- Full-stack capability (front-end frameworks such as React/Vue plus back-end services on cloud infrastructure such as AWS/GCP) sufficient to ship complete features independently.

##### Nice-to-have

- Experience with Vertex AI or equivalent multi-model cloud AI platforms.

- Familiarity with prompt-management and observability tooling such as Braintrust, LangFuse, or MCP-based systems.

- AI Tooling Proficiency: comfort using AI tools to optimize day-to-day work (drafting, analysis, research, automation), with the ability to recommend effective AI use and identify workflow improvements for the team.

- Familiarity with Docker and Git version control.

- Experience consuming and integrating third-party APIs reliably and securely.

##### What we offer

- A High-Impact Environment

- Commitment to Professional Development

- Flexible and Collaborative Culture

- Global Opportunities

- Vibrant Community

- Total Rewards

*Specific benefits are determined by employment type and location.*

Find out more about our culture [here](https://www.instagram.com/wizelineglobal/).

---

Source: WIZELINE's own career page, read by RemJobs. Canonical HTML version: https://www.remjobs.works/job/wizeline-ai-engineer-73464f2d-58cd-4f4f-9f82-e0d81940b649