Senior Software Engineering Manager

Vectra•Austin, TX

About The Position

Vectra is seeking a Senior Software Engineering Manager to lead key areas of its Platform engineering organization. The Platform team is responsible for building and operating foundational software, infrastructure, and tooling that supports Vectra's products, customers, support teams, and engineering teams. This role involves leading high-performing engineering teams focused on critical platform capabilities, including appliance software, cloud infrastructure, deployment systems, operational tooling, service reliability, and developer experience. The successful candidate will collaborate closely with Product, Security, Support, SRE, Cloud, Detection, and other engineering leaders to deliver reliable, secure, and scalable systems. This is a senior management position requiring a blend of strong technical judgment, operational discipline, people leadership, and cross-functional execution.

Requirements

5+ years of engineering management or technical leadership experience, including ownership of production software, infrastructure, or platform systems.
Experience leading teams that deliver reliable, secure, and scalable software.
Strong technical judgment with the ability to discuss architecture, design, code quality, operations, and delivery tradeoffs.
Experience with modern software engineering practices including code review, source control, CI/CD, automated testing, release management, and operational readiness.
Strong Linux/Unix proficiency.
Experience managing Agile delivery practices such as sprint planning, retrospectives, roadmap planning, and project visibility.
Ability to lead cross-team initiatives with complex dependencies and ambiguous ownership boundaries.
Strong communication, organizational, decision-making, and stakeholder management skills.
Demonstrated ability to mentor, motivate, and grow engineers and technical leads.

Nice To Haves

Hands-on experience with AWS, Azure, Kubernetes, Docker, Terraform, GitHub Actions, Jenkins, Packer, or similar platform tooling.
Experience with Linux internals, Debian packaging, AppArmor, cgroups, networking, iptables/nftables, or OS-level security.
Experience with Python, Go, C++, or systems/backend development.
Experience operating production environments and improving reliability, availability, security, and deployment safety.
Experience applying AI-assisted tooling, automation, or developer productivity improvements to engineering workflows.
Interest in using AI to improve software delivery, operational insight, documentation quality, incident analysis, or supportability.
Experience with telemetry systems including metrics, logs, traces, dashboards, and alerting.
Experience with appliance software, virtual appliances, customer-deployed infrastructure, or hybrid cloud products.
Knowledge of networking, cybersecurity, threat detection, or security operations.

Responsibilities

Lead and grow one or more engineering teams responsible for foundational platform capabilities.
Provide direct management, coaching, career development, and performance feedback for engineers and technical leads.
Drive predictable delivery through clear planning, ownership, estimation, Jira hygiene, retrospectives, and consistent follow-through.
Partner with Product Management and engineering leadership to define priorities, clarify requirements, and make thoughtful tradeoffs.
Participate in architecture discussions and guide technical direction across platform systems.
Own operational excellence for team-owned services, including reliability, security, incident response, observability, and root-cause follow-up.
Improve platform services consumed by internal engineering teams and customer-facing products.
Identify opportunities to improve engineering efficiency through AI-assisted development, automation, and better internal tooling.
Encourage responsible use of AI tools for code understanding, test generation, documentation, operational analysis, and repetitive workflow automation.
Partner with engineering leaders to evaluate where AI can reduce toil, improve delivery predictability, and help teams move faster without compromising quality, security, or maintainability.
Ensure production deployments are fast, reliable, secure, and well-supported by automation.
Help define and mature service ownership, operational scorecards, and platform standards across teams.
Partner with recruiting to hire, onboard, and retain strong engineering talent.
Communicate clearly with senior leaders about progress, risk, delivery health, and investment needs.