Senior Manager, Software Tools Development

Job description

Job responsibilities

• 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…
• 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…
• 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.

Job requirements

• 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.
• 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.