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AG
Agilent

Senior Applied AI Engineer, Agentic Systems

LocationSpain-Barcelona
Work modeon-site
Typefull-time
DepartmentR&D
Company size10,000+ people
First seen1w ago
Last seen20h ago
Job Description
About the company
Agilent helps laboratories around the world advance scientific discovery, diagnostics, and applied market solutions through instruments, software, consumables, services, and deep domain expertise.
About the role
As a Senior Applied AI Engineer, Agentic Systems, you will be an AI engineering SME within a cross-functional AI pod, working alongside data engineers, domain experts, business stakeholders, and platform teams. Your role is to design, build, deploy, and govern AI solutions that solve real scientific, service, commercial, and operational challenges across the enterprise.
You will work directly with the end users to understand their workflows, translate business needs into production-grade AI solutions, and ensure those solutions are reliable, observable, reusable, and responsible.
This role goes beyond prototyping. You will build AI agents, RAG applications, orchestration patterns, evaluation frameworks, and reusable skills that become part of Agilent’s broader AI ecosystem.
You do not need to know Agilent’s internal AI platform terminology on day one. We are looking for someone with strong software engineering foundations, experience delivering AI applications into production, and a passion for building practical solutions that create measurable business value.
What you will do:
•
Define the architecture and build approach for the pod’s use case, selecting appropriate agents, RAG, retrieval, and orchestration patterns; designs are reviewed with the Head of Agentic AI Platform Engineering to ensure alignment with reference patterns and platform standards.
•
Build reusable AI skills and integrations using shared platform services and established integration patterns rather than one-off solutions, ensuring components are independently testable and designed for reuse, with appropriate identity, access, and governance controls.
•
Embed evaluation, testing, and observability into delivery from the first sprint, defining benchmark sets with domain experts and establishing regression testing and production monitoring before launch.
•
Implement AI solutions in accordance with security, compliance, and governance requirements, including risk-based controls and human-in-the-loop approval points for regulated or GxP-relevant use cases.
•
Contribute reusable skills, orchestration patterns, and evaluation assets back to the broader AI platform, documenting them for future teams and designing with the second consumer in mind.
•
Partner with and upskill domain SMEs and business practitioners within the pod, helping them sustain AI solutions and providing feedback back to improve platform capabilities over time.
What success looks like in year one
•
The pod’s agentic system is live in production within the domain workflow, with documented governance, identity controls, and human-in-the-loop processes where required.
•
Evaluation coverage is established for critical AI behaviors, with testing, monitoring, and observability embedded into the delivery lifecycle.
•
Multiple reusable skills, orchestration patterns, or evaluation assets created by the pod have been adopted, reused, or positioned for reuse across additional use cases.
•
A rotating SME or business practitioner from the pod has increased their AI capability through active contribution to the solution and ongoing adoption of AI-enabled ways of working.
Qualifications
Technical Expertise
•
Full-stack engineering strength with demonstrated LLM application experience in production
•
Experience building agents, RAG solutions, evaluation frameworks, observability capabilities, and deployment processes, not just prototypes.
•
Working familiarity with MCP or equivalent tool-use protocols, and the architectural judgement to build composable systems under a registry discipline rather than one-off integrations.
Domain and Delivery Mindset
•
High agency and tolerance for ambiguity; comfortable being the senior engineer in a room of scientists, service leaders, or commercial operators, treating their expertise as a critical input to solution design.
•
Experience or genuine willingness to operate within regulated environments; you understand why an audit trail is a feature, not a constraint.
Communication and Influence
•
Communication strong enough to demo to a VP and debug with a bench scientist in the same afternoon.
•
Excellent communication and the ability to influence**.** You write and speak clearly, adapt your style to different audiences, and build credibility through clarity rather than authority.
Curiosity and Growth Mindset
•
Curiosity about AI, including both its opportunities and its limitations. You stay informed about emerging approaches while maintaining healthy skepticism and focus on responsible implementation.
•
A lifelong learner who continuously adapts, expands skills, and embraces new ways of working in a rapidly evolving field.
Education and Seniority
•
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Information Systems, or related field, or equivalent practical experience.
•
Typically, at least 8+ years of relevant experience for entry to this level.
Additional Details
Benefits
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/locationsAgilent 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
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