Senior AI-Driven Scientific Workflow Engineer

Agilent Technologies

Glostrup Kommune

On-site

DKK 900,000 - 1,200,000

Full time

4 days ago

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Job summary

Agilent Technologies is seeking a Senior AI & Scientific Workflow Automation Engineer to shape automation across an R&D organization focused on regulated IVD instruments and reagents. You will translate workflows into AI-enabled, validated solutions with strong governance and repeatability.

You will collaborate with scientists and project teams to drive scalable automation, implement reusable frameworks, and develop digital tools using Python, Copilot, and Power Platform, all to strengthen

Qualifications

A degree in engineering, computer science, data science, bioinformatics, biotechnology, laboratory science, or a related field.
Experience designing and implementing AI-enabled workflows using LLMs and generative AI APIs.
Experience developing agentic or tool-enabled AI workflows, integrating with applications, APIs, data sources, or automation tools to complete structured tasks.
Experience applying guardrails, human-in-the-loop controls, and risk-based approaches to ensure AI-enabled workflows are reliable, transparent, and appropriate for their intended use.
Familiarity with retrieval-augmented generation (RAG) and methods for grounding AI solutions in trusted scientific, technical, or enterprise information.
Ability to translate scientific needs, laboratory workflows, and process challenges into fit-for-purpose automated, digital, or AI-enabled solutions that are robust, reusable, and well documented.
Ability to work independently, set priorities, and make sound technical decisions with incomplete or ambiguous information.
Understanding methods for evaluating and monitoring AI solutions, including accuracy, reliability, traceability, and appropriate testing of AI-generated outputs.
Strong communication and collaboration skills, with the ability to influence, advise, and explain complex technical topics clearly to technical and non-technical stakeholders.

Responsibilities

Partner with scientists and domain experts to understand workflows, data flows, decision points, acceptance criteria, compliance needs, and documentation requirements.
Translate scientific and operational needs into validated and AI-enabled solutions for regulated workflows, including selecting when AI, conventional software automation, or a combined approach is most appropriate.
Identify, shape, and lead automation initiatives from concept to implementation, including objectives, priorities, stakeholders, deliverables, risks, technical design, documentation, and adoption.
Define scalable approaches, reusable frameworks, and best practices that move solutions beyond one-off demonstrations.
Develop digital tools using technologies such as Python, AI-assisted development tools, Microsoft Copilot, Power Platform, analytics, visualization tools, and approved enterprise technologies.
Create solutions for structured data collection, calculations, result evaluation, graphing, summaries, report generation, and decision support.