Job Description

We are looking for technically strong, pragmatic engineers with a primary focus on AI, including hands-on experience with Generative AI and large language models (LLMs). Candidates should also bring solid software engineering practices and a good data background, enabling them to build, deploy, and operate AI-driven solutions in production. We value engineers who collaborate openly, adapt quickly, and focus on delivering practical, usable outcomes.

Soft Skills

• Collaboration & Ownership with Alignment
• Share work early and often, making it visible through docs, demos, and incremental PRs
• Own deliverables following team architecture and workflows
• Communicate decisions, assumptions, and trade-offs clearly to the team
• Avoid working in isolation on critical paths; seek alignment when decisions impact others
• Curiosity & Bias to Action
• Experiment, validate quickly, and iterate based on frequent stakeholder and team feedback
• Suggest improvements grounded in problem-solving rather than tech preference
• Balance exploration with delivery, avoiding over-engineering early
• Pragmatism & User-Centric Thinking
• Optimize for Analytics and Trading adoption, clarity, and trust
• Make sensible trade-offs to deliver usable value early, even if the solution isn’t yet “perfect”
• Adaptability
• Open to feedback and able to adapt as the team and project scale in communication, scope, and technical direction

Hard Skills

• Data & Analytics Engineering
• Strong SQL and experience working with large analytical datasets
• Familiarity with distributed data platforms (e.g., Spark, Trino, Databricks)
• Understanding of data modelling, joins, aggregations, and performance trade-offs
• MLOps & AI Platform Operations
• Experience operationalizing ML and LLM-based systems in production environments
• Familiarity with model lifecycle management (training, versioning, deployment, rollback)
• Understanding of monitoring and observability for ML systems (performance, drift, data quality)
• Experience with automation around pipelines, evaluations, and deployments
• Awareness of scalability, reliability, and cost considerations for AI workloads
• Evaluation, Reliability & Safety
• Understanding of AI evaluation approaches (offline tests, benchmarks, qualitative review)
• Familiarity with logging, monitoring, and debugging AI-driven systems
• Awareness of common AI risks (hallucinations, bias, drift) and mitigation strategies
• Software Engineering Practices
• Strong coding fundamentals and testing discipline
• Experience with CI/CD pipelines and production environments
• Comfortable working with evolving requirements and iterative delivery

Qualifications

• Demonstrated +5 years of experience in data engineering and AI/system development in a production environment
• Proven ability to ship iterative, user-focused solutions with attention to reliability and safety
• Strong communication skills and a collaborative mindset

Nice to Have

• Experience in analytics or trading domains
• Experieånce with vector databases, retrieval-augmented generation (RAG), or LM-based tooling in production
• Hands-on experience with AWS, including designing and operating production-grade cloud infrastructure

Location:

Madrid

Office presence required: Yes (hybrid)

Frequency: 3 times a week at the office

Some of the benefits you’ll enjoy working with us:

• A highly competitive compensation package.
• Medical insurance.
• The chance to join an organization with triple digit growth that is changing the paradigm on how software products are built.
• The opportunity to form part of an amazing, multicultural community of tech experts.

Come and join our #ParserCommunity.

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