
AI Engineering & Data Foundations
Agilent Technologies1 hour ago
Barcelona, SpainSenior
Responsibilities
- Build production AI applications, agents, and AI-enabled workflows.
- Design retrieval foundations using retrieval-augmented generation, vector search, semantic enrichment, and knowledge assets.
- Develop reusable AI-ready data products with strong quality, governance, lineage, and reuse foundations.
- Create reusable engineering capabilities, patterns, and assets that accelerate enterprise AI use cases.
- Apply AI evaluation, monitoring, observability, and governance practices to ensure reliable outcomes.
- Partner with domain experts and business stakeholders to translate workflows and needs into scalable technical solutions.
- Use AI-assisted approaches such as metadata generation, entity resolution, and content classification to improve data quality and discoverability.
- Collaborate in cross-functional AI pods with engineers, domain experts, business stakeholders, and platform teams.
Requirements
- Experience building software, AI, platform, or data solutions in production environments.
- Familiarity with modern AI technologies, data platforms, and enterprise architectures.
- Strong engineering foundations with a focus on quality, reliability, and reusability.
- Experience or interest in AI engineering, AI agents, agentic workflows, retrieval-augmented generation, LLM application development, AI evaluation, observability, orchestration, or production AI deployment.
- Experience or interest in AI data engineering, data products, data contracts, AI-ready data foundations, metadata management, semantic enrichment, retrieval architecture, vector databases, graph technologies, data quality, governance, or lineage.
- Experience or interest in full-stack software development, distributed systems, APIs, cloud platforms, enterprise integration, platform engineering, or identity, access, and governance controls.
- Typically 6+ years of relevant experience in software engineering, AI engineering, data engineering, machine learning, platform engineering, or related disciplines.
- Bachelor's or Master's degree, or equivalent practical experience.
- Strong problem-solving, communication, collaboration, stakeholder partnership, and continuous-learning skills.
Benefits
- Full-time schedule with a day shift.
- 10% travel required.
- No end date stated for the position.
- Pay and benefits vary by country and are determined by role, level, location, skills, experience, and education or training.
Categories
AI ApplicationsData Engineering