- Architect, design, and implement scalable hybrid cloud solutions for transactional, analytics and RAD workloads.
- Write and review high-quality code, ensuring adherence to best practices and standards.
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
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.
Collaborate with development leads and cross-functional teams to deliver robust solutions.
- Conduct code reviews and provide constructive feedback to drive technical excellence.
- Present technical concepts and project updates to senior stakeholders.
- Prioritize tasks effectively, balancing urgent needs with strategic progress.
- Mentor and support team members, fostering a collaborative and helpful environment.
Required qualifications, capabilities and skills:
- Formal training or certification on hybrid cloud architecture concepts and 5+ years applied experience.
- Proven experience in hybrid cloud architecture (AWS, Azure, GCP, or private cloud).
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
- Deep understanding of distributed systems, data pipelines, and analytics platforms.
- Experience with CI/CD, DevOps, and modern software engineering practices.
- Excellent interpersonal and presentation skills.
- Demonstrated ability to work with development leads and senior stakeholders.
Preferred qualifications, capabilities and skills:
- Action-oriented, decisive, drives results systematically.
- Strong coding skills in languages such as Java, Python, React or similar.
- Skilled at assessing risk and making decisions with a holistic, big-picture perspective.
- Demonstrates a can-do attitude and leads by example.
- Detail-oriented, able to distinguish between important and urgent tasks.
- Prioritizes helpfulness, mentorship, and team development.
- Acts with integrity.
