Zoox seeks a Senior Manager of SW Tools Development to lead hybrid AI and infrastructure teams, combining LLM/agent engineering with test infrastructure and automation. The role requires managing managers, driving adoption of internal tools, and ensuring reliable delivery across engineering and business stakeholders.
- Compensation
- USD 245,000–348,000 / year
What you need
- 6-8+ years of experience in software engineering or applied AI
- Experience managing managers and/or multiple engineering teams with accountability for delivery and quality
- Solid, practical knowledge of LLMs and applied AI with experience delivering AI-driven solutions to real business problems
- Experience designing and shipping production AI agent or automation systems including architecture, tool/integration contracts, and validation processes
- Experience with test infrastructure, data pipeline design, and process automation
- Proven track record leading cross-functional programs and presenting to senior stakeholders
What you will own
- Lead and grow multiple engineering teams spanning AI-powered tools/agents and test infrastructure, data pipelines, and process automation
- Manage managers and senior engineers while holding the organization accountable for delivery and quality
- Set unified roadmap balancing new AI capabilities with infrastructure and automation needs
- Design architecture, quality gates, and release processes for validated, secure, and reliable production systems
- Partner cross-functionally with engineering, operations, and business leadership to align priorities and drive adoption
- Demo team tools to internal stakeholders and grow the portfolio of supported products and use cases
Core skillsSoftware engineeringLLM and applied AIAI agent and automation systemsTest infrastructureData pipeline designProcess automationSystem architectureQuality assuranceRelease managementCross-functional leadership
We're looking for a Senior Manager of SW Tools Development to lead an organization built on two closely connected pillars: AI-powered tools and agents, and the test infrastructure, data pipelines, and process automation that engineering and business teams rely on every day. You'll bring deep knowledge of large language models (LLMs) and applied AI, and use it not only to build new AI-driven products but to find where AI can meaningfully upgrade test infrastructure, data pipelines, and automation — the overlap between these areas is where some of your team's highest-leverage work happens. Beyond building the tools, you'll be the face of your organization's products internally — demoing capabilities, winning over new adopters, and growing the portfolio of tools your team owns. You will manage multiple engineering teams (including managers), partner cross-functionally with stakeholders across the business, and build the processes that let your tools ship safely and reliably at scale.In this role, you will:
Lead and grow multiple engineering teams spanning AI-powered tools/agents and test infrastructure, data pipelines, and process automation, managing and mentoring managers and senior engineers, and holding your organization accountable for delivery and quality across both areas.
Set a unified, prioritized roadmap across your organization that balances new AI agent/tool capabilities with test infrastructure, data pipeline, and process automation needs — with a sharp eye for where applying LLMs to automation, pipelines, or test systems creates outsized leverage.
Design and enforce the architecture, quality gates, and release processes that ensure tools, pipelines, and AI agents are validated, secure, and reliable before reaching production.
Partner cross-functionally with engineering, operations, and business leadership across the company to align priorities, scope integrations, and drive adoption of new tooling at an organizational level.
Demo and present your team's tools to internal stakeholders, attract new internal customers, and grow the portfolio of products and use cases your team supports.
Build and continuously improve the processes (planning, release management, quality assurance, reporting) that let your organization ship tools predictably and at scale.
Qualifications:
6-8+ years of experience in software engineering or applied AI, including experience managing managers and/or multiple engineering teams, with accountability for delivery and quality across an organization.
Solid, practical knowledge of LLMs and applied AI, with experience identifying and delivering AI-driven solutions to real business problems.
Experience designing and shipping production AI agent or automation systems, including defining architecture, tool/integration contracts, and validation processes.
Experience with test infrastructure, data pipeline design, and process automation, including recognizing where AI/LLM techniques can improve or extend these systems.
Proven track record leading cross-functional programs and presenting to senior stakeholders, aligning priorities and driving adoption across teams and functions that don't report to you.
Bonus Qualifications:
Experience operating AI-driven automation or triage tools in production with measurable quality/accuracy metrics.
Background in complex, safety-critical, or high-uptime operational environments.
Experience managing distributed or contractor engineering teams.
