Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Own the design, delivery, and operation of enterprise-scale infrastrucutre services from architecture through production
Write and review production code, maintaining a hands-on apporach and setting the bar for engineering quality
Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
Formal training or certificaiton on software engineering concepts and 5+ years applied experience
Hands-on practical experience delivering system design, application development, testing, and operational stability
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Advanced hands on expereince engineering with production code experience in one or more programming industry-standard language(s) and framework(s) (e.g., Python, GO, Java, C++, Rust, React, Full Stack, etc.)
Deep experience building and operating systems in at least one infrastructure domain (cloud, networking, compute, storage, security, or data infrastructure)
Experience running production systems at scale, including on-call ownership, indcient response, and desinging for reliability and operability
Understands how to lead and mentor engineers, with setting technical direction
Proficiency in automation and continuous delivery methods
Proficient in all aspects of the Software Development Life Cycle
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
Experience across multiple infrastructure domains or programming languages
Track record of reducing operational toil and cost through automation and better engineering
Experience adopting AI-native engineering practices at team or organizational scale
Prior experience in regulated or large-scale enterprise environments
Experience with greenfield builds and establishing engineering culture
Ability to influence engineering patterns beyond the immediate team
