Lead Infrastructure Engineering

Job responsibilities

• pplies technical expertise and problem-solving methodologies to projects of moderate scope contributes to the NDSS platform strategy, roadmap, and lifecycle management.
• Governs and maintains network device security standards and baseline controls.
• Oversees creation, approval, and lifecycle of device security templates and policies.
• Ensures integration with compliance and findings platforms (e.g., FARM) for audit reporting.
• Drives continuous compliance monitoring, reporting, and remediation workflows.
• Leads cross-functional coordination with engineering, operations, and risk/control teams.
• Ensures audit readiness with full traceability from standards through enforcement to reporting.
• Drives automation and scale across configuration enforcement and policy validation leads transformation initiatives to improve efficiency, security posture, and risk reduction.
• Defines and tracks key performance and compliance metrics across the NDSS platform.
• 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.

Required qualifications, capabilities, and skills

• Formal training or certification on infrastructure disciplines concepts and 5+ years applied experience.
• Strong expertise in network security controls (AAA, access control, encryption, SNMPv3, etc.).
• Experience writing Ansible playbooks and relevant years of software development (Python).
• Demonstrated knowledge of data parsing and analysis, including regular expression parsing.
• Hands-on experience with configuration management and automation tooling.
• Deep understanding of security compliance frameworks and audit processes.
• Experience with compliance reporting and findings management systems.
• Demonstrated ability to operate in highly regulated environments (e.g., financial services) strong cross-functional collaboration and communication skills.
• Proven ability to manage multiple priorities and deliver in a fast-paced environment.
• 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

• Obtain relevant certifications (e.g., CISSP, CISM, CCNP/CCIE).
• Apply experience operating within financial services or other highly regulated industries.
• Demonstrate advanced automation expertise across configuration enforcement and policy validation.