Jobs at Agilent Technologies

Provides tier 3 technical support for Agilent diagnostic and acquisition software, including feature development, defect resolution, debugging, validation, testing, and technical documentation. Collaborates with R&D, marketing, sales, QA, manufacturing, and customers to define requirements and support product releases. Delivers technical training to field and remote service engineers. Requires software engineering expertise in C or C++, RTOS, concurrent programming, Python, web servers, REST APIs, and analytical instruments, with LC and/or MS experience.

Leads the design and delivery of governed, business-ready data products, dimensional models, semantic assets, and KPI frameworks for Global Operations. Builds scalable lakehouse transformations using SQL, Python, and PySpark; establishes data quality, lineage, metadata, testing, CI/CD, monitoring, and security practices; and partners with business and technology stakeholders across supply chain, manufacturing, quality, and regulatory functions. Develops AI-ready data foundations supporting analytics, machine learning, generative AI, and executive reporting.

Leads the strategy, roadmap, development, and continuous enhancement of executive decision-intelligence products. Builds Power BI and Microsoft Fabric dashboards, scorecards, semantic models, scenario-planning applications, and predictive analytics solutions. Integrates ERP and disparate data sources using Python and SQL, applies AI/ML techniques, and partners with global operations leaders across supply chain, manufacturing, quality, and regulatory functions. Translates complex operational data into scalable, user-centric insights that improve executive decision-making and enterprise performance.

Own the strategy, roadmap, backlog, requirements, lifecycle, and release planning for LC/MS acquisition software, instrument control, and software drivers. Partner with R&D, quality, support, marketing, and commercial teams to deliver compliant, reliable scientific software. Lead market research, workflow definition, compatibility management, defect prioritization, product launches, and customer-impacting issue resolution across LC/MS and selected GC/MS workflows.

Leads enterprise transformation for a global software division in partnership with the GM. Owns the integrated transformation plan, AI adoption, operating rhythm, delivery metrics, risk escalation, cross-functional alignment, business operations, and executive communications. Drives platform modernization, engineering productivity, accountability, and measurable business outcomes across a global matrixed organization.

Own the architecture of scientific data discovery and access across catalogs, search, federated GraphQL, application data services, and event-driven pipelines. Define schemas, contracts, service boundaries, modernization paths, performance targets, and governance controls for AI and application consumers. Partner closely with engineering on implementation, recovery and backfill, integrations, decision records, and proof-of-concept development across cloud, hybrid, and on-premises environments.

Leads strategy, growth, roadmap, lifecycle management, and commercialization for Agilent’s HRMS portfolio, including LC/Q-TOF systems and workflow solutions. Responsibilities include identifying market opportunities, defining product requirements, guiding development, building business cases, leading global launches, developing positioning, engaging customers and industry experts, and influencing cross-functional stakeholders across R&D, sales, marketing, finance, manufacturing, and support.

Lead global internal communications strategy, develop employee messaging, collaborate cross-functionally, manage ESG communications, and oversee crisis communication planning.

Leads Agilent’s global enterprise public-relations strategy, including media relations, social media, M&A communications, crisis communications, and investor-support messaging. Manages a global team and partners with executives, finance, brand, and cross-functional leaders to deliver consistent external communications, strengthen corporate reputation, communicate business updates, and engage customers, investors, analysts, employees, and media.

Serve as the primary finance partner for the Productivity Solutions Division, leading planning, forecasting, performance management, and financial analysis to drive recurring revenue growth and profitability. Partner with commercial, product, R&D and functional leaders on pricing, customer retention, investments, and resource allocation. Leverage FP&A COE, data, automation and AI tools to improve forecasting and executive decision support.

Design, develop, validate, and optimize algorithms for mass spectrometry data analysis. Responsibilities include feature finding, signal processing, peak detection, pattern recognition, machine learning, numerical modeling, production software development, algorithm validation, performance benchmarking, and collaboration with software engineers, scientists, application experts, and customers.

Provides technical leadership for AI engineering and SDLC automation across a platform engineering organization. Designs and delivers AI agents, copilots, developer tools, and automated workflows integrated into CI/CD pipelines and engineering platforms. Establishes responsible AI governance, safety guardrails, evaluation methods, and secure integration patterns. Leads cross-functional initiatives, mentors engineers, drives adoption, and measures improvements in productivity, quality, reliability, and developer experience.

Owns global payroll delivery, statutory compliance, controls, vendor management, and service standards across all regions. Leads global payroll and time-tracking consolidation, including operating-model design, technology selection, country deployments, governance, and change management. Establishes AI and automation strategies to improve accuracy, reduce manual work, and strengthen preventive controls. Manages distributed payroll leadership teams and partners with Finance, Tax, Legal, Treasury, HR Technology, auditors, and regulators.

Leads distributed Software Quality Engineering and Software QC teams, setting priorities, developing talent, and allocating resources. Partners with engineering, product, and regulatory teams on verification and validation strategies. Oversees manual and automated testing, risk management, defect resolution, compliance, traceability, and test evidence. Drives test automation, shift-left quality, continuous improvement, and strategic initiatives while ensuring laboratory software meets customer, quality, reliability, and regulatory requirements.

Supports a VP by managing complex global calendars, travel, meetings, communications, confidential information, leadership-team operations, and follow-through. Coordinates events, expenses, vendors, organizational resources, and strategic initiatives while tracking milestones, budgets, headcount, and metrics. Improves workflows through digital tools, AI, and automation, and serves as a trusted liaison to executives and global stakeholders.

Develop and maintain advanced inventory and supply planning models, inventory optimization targets, scenario analyses, dashboards, and KPIs. Use Python, SQL, BI tools, predictive modeling, and machine learning to support supply planning, S&OE/S&OP, demand-supply coverage, capacity constraints, and inventory health. Partner with planning teams to improve data quality, automation, governance, model reliability, and executive decision-making.

Lead AMG Strategy & Program Management as a trusted advisor, managing strategic planning, project portfolio, operational excellence, and team development to achieve innovative results.

Lead R&D hardware development for Agilent's automation platforms, managing multidisciplinary teams across mechanical, electrical, fluidics, motion control, and systems engineering. Drive product strategy, end-to-end program execution, manufacturability, lifecycle management, and cross-functional collaboration to commercialize laboratory automation solutions.

Lead an enterprise AI product pod to define use cases, KPIs, scope, and adoption; coordinate cross-functional stakeholders (Legal, Quality, IT/Security); ship LLM/agent/RAG solutions into real workflows; produce reusable Fabric assets; manage roadmap, telemetry-driven adoption, and portfolio reporting.