Note: The job is a remote job and is open to candidates in USA. Agilent Technologies is seeking a Lead in AI Engineering & SDLC Automation to define and lead their AI-enabled engineering automation strategy. The role involves leading a team to enhance developer productivity and software delivery through AI-assisted engineering capabilities and workflow automation.
Responsibilities
- 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 in engineering workflows
- Partner with DevSecOps, Developer Experience, Security, QE, IT, and engineering teams to embed automation into software delivery practices
- 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 for AI-enabled engineering automation, including productivity, adoption, toil reduction, quality, reliability, and developer experience
Skills
- 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
Benefits
- Plus eligibility for bonus
- Plus eligibility for stock
- Plus eligibility for benefits
- Option to work remotely
Company Overview
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