Lead, AI Engineering – SDLC Automation

This is a fully remote position, open to applicants in United States, +3 more states.

📋 Description

• Lead and nurture the AI Engineering & Automation team tasked with AI-assisted SDLC automation, developer workflow integration, and enhancing engineering productivity tools.

• Set team priorities, determine resource requirements, establish operating rhythms, define performance expectations, and create execution strategies.

• Own the strategy for AI-enabled engineering automation within PSD, encompassing tool selection, integration, adoption, measurement, and ongoing improvement.

• Provide AI-assisted engineering tools, agentic workflows, copilots, and workflow automation that yield measurable productivity enhancements.

• Integrate AI automation within CI/CD pipelines, developer paved roads, engineering workflows, and platform services.

• Establish governance frameworks, safety measures, evaluation criteria, usage standards, and secure integration practices for responsible AI implementation.

• Collaborate with DevSecOps, Developer Experience, Security, QE, IT, and various engineering teams.

• Prioritize investments in AI automation based on productivity gain, developer experience, quality, reliability, security, cost, and platform strategy.

• Propel cross-organizational adoption through enablement, documentation, training, feedback mechanisms, and measurable adoption strategies.

• Address conflicting priorities related to engineering productivity, security, reliability, cost, and responsible AI practices.

• Define and monitor success metrics including productivity, adoption rates, toil reduction, quality, reliability, and developer satisfaction.

• Support Agilent Technologies' mission in laboratory and clinical technologies, life science research, diagnostics, and safety applications.

⛳️ Requirements

• Typically possess 5+ years of experience in formally or informally leading people, projects, and/or programs.

• Hold a Bachelor’s or Master’s degree or equivalent experience.

• Have a robust background in AI-enabled engineering, platform engineering, DevOps, developer productivity, workflow automation, or SDLC automation.

• Demonstrated experience in leading teams, programs, or cross-functional initiatives within complex software engineering environments.

• Skilled at translating organizational strategy into actionable roadmaps, execution plans, governance frameworks, and measurable results.

• Familiarity with AI agents, copilots, AI-assisted software engineering tools, ML-driven automation, or agentic workflow automation.

• Strong understanding of CI/CD, SDLC tools, developer workflows, engineering productivity tools, and secure integration practices.

• Knowledge of responsible AI adoption, AI governance, usage controls, safety measures, and secure deployment methodologies.

• Ability to influence senior stakeholders across engineering, product, security, QE, IT, and platform teams.

• Experience facilitating adoption, enablement, and behavioral change among distributed engineering teams.

• Capable of balancing speed, productivity, quality, reliability, security, cost, and responsible AI utilization.

• Strong analytical and communication skills, with the ability to convert productivity and adoption insights into actionable roadmap choices.

• Occasional travel may be necessary.

• Day shift position.

🏝️ Benefits

• Eligibility for a bonus.

• Stock options.

• Comprehensive benefits package.

• Opportunity to work remotely.

• Commitment to an inclusive workplace.

• Disability assistance available during the application or interview process.