Quick Summary
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).
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.
Follow us on Linkedin
Location & Eligibility
Listing Details
- Posted
- January 19, 2026
- First seen
- May 21, 2026
- Last seen
- May 21, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 14%
- Scored at
- May 21, 2026
Signal breakdown
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