Lead Infra Engineer - PKI - Public Key Infrastructure.
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About this role
Job responsibilities
- Applies technical expertise and problem-solving methodologies to projects of moderate scope and executes creative solutions for design, development, and technical troubleshooting for problems of moderate complexity
- Uses enterprise-authorized AI capabilities within the work environment to accelerate infrastructure analysis and design documentation, validating outputs and handling operational data according to sensitivity and security requirements.
Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
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.
- Drives a workstream or project consisting of one or more infrastructure engineering technologies and works with other platforms to architect and implement changes required to resolve issues and modernize the organization and technology processes
- Strongly considers upstream and downstream data and systems or technical implications and advises on mitigation actions
- Applies reuse-first, AI-assisted practices within delivery and automation routines to identify recurring issues and validate remediation options, ensuring changes are traceable/auditable and aligned to resiliency and security expectations.
- Drive automation of PKI processes, including certificate issuance, renewal, and revocation.
- Ensure the security and integrity of TLS certificates and cryptographic operations.
- Monitor and enhance PKI system performance, availability, and resilience
- Formal training or certification on infrastructure engineering concepts and 5+ years applied experience
- Proven experience with ADCS, EJBCA, and HSMs (e.g., Safenet/Gemalto).
- Deep knowledge of one or more areas of infrastructure engineering such as: hardware, networking terminology, databases, storage engineering, deployment practices, integration, automation, scaling, resilience or performance assessments
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
- Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity.
- Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations.
- Deep knowledge of one specific infrastructure technology and scripting languages
- Deep knowledge of cloud infrastructure and multiple cloud technologies with the ability to operate in and migrate across public and private clouds
- Experience with EJBCA and DCLM solutions such as Key Factor / Venafi
Company
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