AI Engineering & Data Foundations

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