Lead, AI Engineering – SDLC Automation

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🔥 26 minutes ago

🌐 United States, Germany, +1 more countries – Remote

🇺🇸 United States – Remote 🇩🇪 Germany – Remote 🇪🇸 Spain – Remote

🏄 California – Remote

🏄 California – Remote

💵 $168.2k - $315.3k / year

⏰ Full Time

🟠 Senior

🤖 AI Engineer

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Agilent Technologies

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1999

🍽️ Food & Beverage

🏥 Healthcare

💼 Consulting

💰 $500M Post-IPO Debt on 2019-09

Food & Beverage • Healthcare • Consulting

Agilent Technologies is a global leader in the field of analytical and laboratory instruments. The company offers a diverse range of products and solutions, including gas and liquid chromatography, mass spectrometry, lab supplies, and software and informatics. Agilent serves various industries, such as biopharma, food and beverage testing, clinical diagnostics, and environmental testing. Additionally, Agilent provides comprehensive services for lab management, maintenance, and instrument repair. They focus heavily on advancing science through sustainable solutions and supporting genomics, pathology, and cancer research with advanced technologies.

📋 Description

• Lead and develop the AI Engineering & Automation team responsible for AI-assisted SDLC automation, developer workflow integration, and engineering productivity tooling • Define team priorities, resource needs, operating cadence, performance expectations, and execution plans • Own the roadmap for AI-enabled engineering automation across PSD, from tool selection and integration to adoption, measurement, and continuous improvement • Deliver AI-assisted engineering tools, agentic workflows, copilots, and workflow automation with measurable productivity uplift • Integrate AI automation into CI/CD pipelines, developer paved roads, engineering workflows, and platform services • Establish governance, safety guardrails, evaluation criteria, usage standards, and secure integration patterns for responsible AI adoption • Partner with DevSecOps, Developer Experience, Security, QE, IT, and engineering teams • Prioritize AI automation investments based on productivity uplift, developer experience, quality, reliability, security, cost, and platform strategy • Drive cross-organization adoption through enablement, documentation, training, feedback loops, and measurable adoption plans • Resolve conflicting priorities across engineering productivity, security, reliability, cost, and responsible AI adoption • Define and track success measures including productivity, adoption, toil reduction, quality, reliability, and developer experience • Support Agilent Technologies' mission in laboratory and clinical technologies, life science research, diagnostics, and safety applications

🎯 Requirements

• Typically 5+ years of experience formally or informally leading people, projects, and/or programs • Bachelor’s or Master’s degree or equivalent experience • Strong background in AI-enabled engineering, platform engineering, DevOps, developer productivity, workflow automation, or SDLC automation • Experience leading teams, programs, or cross-functional initiatives in complex software engineering environments • Experience translating organizational strategy into roadmaps, execution plans, governance models, and measurable outcomes • Experience with AI agents, copilots, AI-assisted software engineering tools, ML-driven automation, or agentic workflow automation • Strong understanding of CI/CD, SDLC tooling, developer workflows, engineering productivity tooling, and secure integration patterns • Understanding of responsible AI adoption, AI governance, usage controls, safety guardrails, and secure deployment patterns • Ability to influence senior stakeholders across engineering, product, security, QE, IT, and platform organizations • Experience driving adoption, enablement, and behavior change across distributed engineering teams • Ability to balance speed, productivity, quality, reliability, security, cost, and responsible AI use • Strong analytical and communication skills, with the ability to translate productivity and adoption insights into practical roadmap decisions • Occasional travel required • Day shift

🏖️ Benefits

• Eligibility for bonus • Stock • Benefits • Option to work remotely • Inclusive workplace • Disability assistance during the application or interview process