EnglishWillDo

AI Engineer

Once For All · Madrid, Spain

No Spanish requiredPosted today
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About Us

Nalanda is a leading Spanish multinational dedicated to bridging the gap between large companies and their suppliers through an innovative digital platform. Our platform streamlines business processes such as document exchange, purchases, invoices, and vital business information. We specialize in coordinating activities between contractors and their suppliers, minimizing costs, time, and risks, while fostering transparent and effective business relationships.

We are a dynamic, forward-thinking company committed to building an inclusive workplace where talent thrives. At Nalanda, we believe that the development of people drives organizational success. Join us as we continue to build a culture of growth, inclusivity, and excellence.

We are also part of Once For All, an international group with a presence in the UK, France, Latin America, and more than 1,000 people working on digital solutions for supply chain management and regulatory compliance.

Role Summary

Own AI initiatives end-to-end — from spotting the right opportunity to a model running reliably in production. You set technical direction, collaborate closely with Product and Engineering, and bring the judgment to know when something is ready to ship and when it needs more work.

Key responsibilities

  • Shape what we build Identify and prioritize high-value AI opportunities together with Product and
  • business stakeholders.
  • Define success metrics and constraints (latency, cost, risk) before building, and choose the simplest approach that meets them — heuristic, classical ML, or generative.
  • Bring informed opinions to the table. We want someone who proposes ideas, not only one who executes them well.
  • Build it right, ship it, keep it healthy Design and train ML/LLM models, and take them all the way into production — APIs, pipelines, monitoring.
  • Set up the monitoring and drift detection that lets the team trust the system once it's live.
  • Iterate based on real usage and metrics, in partnership with Data and Engineering colleagues.
  • Raise the bar for the team
  • Share what you learn — demos, documentation, internal talks — so the team's AI practice improves, not just your own output.
  • Mentor less experienced engineers and review others' work constructively.
  • Work well across Product, Design, Data, and Engineering.

Qualifications

Non-negotiable

  • 5+ years of hands-on ML/AI engineering, with models you've personally taken to production at meaningful scale.
  • Strong Python and software engineering fundamentals — testing, CI/CD, code review.
  • Production experience with LLMs: prompting, RAG, evaluation, cost/latency tradeoffs.
  • Comfortable collaborating across disciplines and working from ambiguous problems without needing everything specified upfront.
  • English at B2 or above.
  • You've owned a model's full lifecycle: training, deployment, monitoring, and the fixes that came after.
  • You've influenced a product decision with AI insight, working alongside non technical stakeholders.
  • You've mentored someone who is now independently effective.
  • Show us systems you've built, the scale they ran at, and the impact they had.

STACK

  • Language: Python
  • LLM & Generative: OpenAI / Anthropic APIs, orchestration frameworks (LangChain, LlamaIndex, or equivalent)
  • MLOps & Data: SQL, Docker, experiment tracking (MLflow or equivalent)
  • Cloud & Infra: AWS (Lambda, RDS, S3, Bedrock or SageMaker), GitLab CI / GitHub Actions
  • Observability: Drift monitoring, latency/cost metrics, structured logging
  • Collaboration: Git, Jira, Confluence

What we offer

Competitive compensation package, with a salary range of €40.000 €65.000 gross per year, depending on experience and fit.

Flexible working time.

️ Teleworking.

️ Intensive working time in summer.

️ Flexible benefits.

A dynamic and inclusive workplace with opportunities for growth and development.

The chance to make a significant impact on our organizational culture and talent strategy.