AI Engineering & Data Foundations

Agilent
Location
Spain-Barcelona
Job Type
Full-time
Posted
September 9, 2026
Views
3

Job Description

Agilent is expanding its AI capabilities across scientific, service, commercial, and operational functions. We are building a team of engineers who can help design, deploy, and scale trusted AI solutions that create measurable business impact.

We're interested in connecting with experienced professionals across AI Engineering, AI Data Engineering, and related technical disciplines who are passionate about applying AI in real-world environments. Depending on your background and interests, opportunities may focus on AI applications, agentic systems, retrieval foundations, AI-ready data products, platform engineering, or the underlying capabilities that enable AI at scale.

You will work within cross-functional AI pods alongside engineers, domain experts, business stakeholders, and platform teams to turn complex business challenges into practical, production-ready solutions.

What You May Work On

  • Building production AI applications, agents, and AI-enabled workflows.
  • Designing retrieval foundations for AI solutions, including RAG, vector search, semantic enrichment, and knowledge assets.
  • Developing AI-ready data products with strong foundations in quality, governance, lineage, and reuse.
  • Creating reusable capabilities, patterns, and assets that accelerate future AI use cases across the enterprise.
  • Applying evaluation, monitoring, observability, and governance practices to ensure reliable AI outcomes.
  • Partnering directly with domain experts to understand workflows and translate business needs into scalable technical solutions.
  • Leveraging AI-assisted approaches such as metadata generation, entity resolution, and content classification to improve data quality and discoverability.

We're Particularly Interested in Professionals with Experience In:

AI Engineering

  • AI agents and Agentic Workflows
  • Retrieval-Augmented Generation (RAG)
  • LLM application development
  • AI evaluation and observability
  • AI orchestration and integration
  • Production AI deployment

AI Data Engineering

  • Data products and data contracts
  • AI-ready data foundations
  • Metadata management and semantic enrichment
  • Retrieval architecture
  • Vector databases and graph technologies
  • Data quality, governance, and lineage

Software & Platform Engineering

  • Full-stack software development
  • Distributed systems and APIs
  • Cloud platforms and enterprise integration
  • Platform engineering
  • Identity, access, and governance controls

Qualifications

What We're Looking For

Technical Expertise

  • Experience building software, AI, platform, or data solutions in production environments.
  • Familiarity with modern AI technologies, data platforms, and enterprise architectures.
  • Strong engineering foundations and commitment to quality, reliability, and reusability.

Domain & Delivery Mindset

  • Strong problem-solving skills and comfort operating in ambiguous environments.
  • Ability to partner closely with business stakeholders, domain experts, and technical teams.
  • An instinct to build solutions that can scale beyond a single project or use case.

Communication & Influence

  • Strong communication skills and the ability to collaborate across technical and non-technical audiences.
  • Ability to explain complex concepts clearly and build credibility through expertise and partnership.

Agilent is expanding its AI capabilities across scientific, service, commercial, and operational functions. We are building a team of engineers who can help design, deploy, and scale trusted AI solutions that create measurable business impact.

We're interested in connecting with experienced professionals across AI Engineering, AI Data Engineering, and related technical disciplines who are passionate about applying AI in real-world environments. Depending on your background and interests, opportunities may focus on AI applications, agentic systems, retrieval foundations, AI-ready data products, platform engineering, or the underlying capabilities that enable AI at scale.

You will work within cross-functional AI pods alongside engineers, domain experts, business stakeholders, and platform teams to turn complex business challenges into practical, production-ready solutions.

What You May Work On

  • Building production AI applications, agents, and AI-enabled workflows.
  • Designing retrieval foundations for AI solutions, including RAG, vector search, semantic enrichment, and knowledge assets.
  • Developing AI-ready data products with strong foundations in quality, governance, lineage, and reuse.
  • Creating reusable capabilities, patterns, and assets that accelerate future AI use cases across the enterprise.
  • Applying evaluation, monitoring, observability, and governance practices to ensure reliable AI outcomes.
  • Partnering directly with domain experts to understand workflows and translate business needs into scalable technical solutions.
  • Leveraging AI-assisted approaches such as metadata generation, entity resolution, and content classification to improve data quality and discoverability.

We're Particularly Interested in Professionals with Experience In:

AI Engineering

  • AI agents and Agentic Workflows
  • Retrieval-Augmented Generation (RAG)
  • LLM application development
  • AI evaluation and observability
  • AI orchestration and integration
  • Production AI deployment

AI Data Engineering

  • Data products and data contracts
  • AI-ready data foundations
  • Metadata management and semantic enrichment
  • Retrieval architecture
  • Vector databases and graph technologies
  • Data quality, governance, and lineage

Software & Platform Engineering

  • Full-stack software development
  • Distributed systems and APIs
  • Cloud platforms and enterprise integration
  • Platform engineering
  • Identity, access, and governance controls

Qualifications

What We're Looking For

Technical Expertise

  • Experience building software, AI, platform, or data solutions in production environments.
  • Familiarity with modern AI technologies, data platforms, and enterprise architectures.
  • Strong engineering foundations and commitment to quality, reliability, and reusability.

Domain & Delivery Mindset

  • Strong problem-solving skills and comfort operating in ambiguous environments.
  • Ability to partner closely with business stakeholders, domain experts, and technical teams.
  • An instinct to build solutions that can scale beyond a single project or use case.

Communication & Influence

  • Strong communication skills and the ability to collaborate across technical and non-technical audiences.
  • Ability to explain complex concepts clearly and build credibility through expertise and partnership.

Curiosity & Growth Mindset

  • Curiosity about AI, both its opportunities and limitations.
  • Commitment to continuous learning in a rapidly evolving field.

Education & Seniority

  • Bachelor's or Master's degree, or equivalent practical experience.
  • Typically, 6+ years of relevant experience in software engineering, AI engineering, data engineering, machine learning, platform engineering, or related disciplines.

Additional Details

This job has a full time weekly schedule.

Our pay ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. During the hiring process, a recruiter can share more about the specific pay range for a preferred location. Pay and benefit information by country are available at: https://careers.agilent.com/locations

Agilent Technologies Inc. is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other protected categories under all applicable laws.

Travel Required

10% of the Time

Shift

Day

Duration

No End Date

Job Function

R&D

Frequently Asked Questions

Where is the job located, and is it remote/hybrid/on-site?
The job is located in Barcelona, Spain. The posting does not specify a remote, hybrid, or on-site work-mode policy.
What are the required qualifications and experience level for this role?
You should have a Bachelor's or Master's degree (or equivalent practical experience) and typically 6+ years of relevant experience in software, AI, data, machine learning, or platform engineering. You also need experience building production solutions, familiarity with modern AI technologies, and strong communication skills.
What are the key responsibilities of this position?
You will build production AI applications, design retrieval foundations (RAG, vector search), develop AI-ready data products, and create reusable capabilities. You will also apply evaluation and monitoring practices, partner with domain experts, and leverage AI-assisted approaches to improve data quality.
What is the salary or compensation range for this role?
Specific pay ranges are determined by role, level, and location. A recruiter can share the specific pay range for your preferred location during the hiring process. Country-specific pay and benefit information is also available on Agilent's careers website.

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Job Information

Source: manual
AI Relevance: 70/100 (Relevant)
Remote Type: onsite
Allowed Locations: Worldwide
Skills & Tags:
agilent machine learning data engineering LLM
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