Director, Software Engineering Management
$221,200–$387,100 year
HybridSanta Clara, California, United States
Job Summary
Lead teams architecting and building assistive, autonomous AI-native products for ITSM and ITOM capabilities, spanning large-scale distributed systems, data ingestion, and agentic feedback loops. Own technical strategy, set architectural direction, and drive evidence-based decision-making through hypothesis formulation, experimentation, and outcome measurement. Hire, coach, and develop engineers and tech leads to build high-performing teams with clear career paths. Collaborate across Product, Design, Security, Operations, Sales, and Customer Success to align on roadmap, release readiness, and field signal. Identify value realization gaps in agentic products, diagnose root causes, and direct targeted improvements to unlock customer productivity. Establish architecture patterns, engineering standards, and operating rhythms specific to your domain.
Required Qualifications
- 15+ years of related engineering experience
- 5+ years leading and managing engineering teams (including managers or team leads), or equivalent practical experience
- Strong experience building and operating large-scale distributed systems, enterprise platforms, workflow systems, data-intensive products, integration frameworks, or cloud-scale infrastructure
- Deep understanding of system design for scale, reliability, observability, fault tolerance, data quality, security, and production readiness
- Strong technical depth in Java, Python, or similar programming languages
- Proven ability to define technical direction, influence architecture across teams, and translate ambiguous product strategy into executable engineering plans
- Demonstrated success hiring, developing, and retaining engineers and engineering leaders, and managing performance, career growth, and team health
- Ability to lead through formal authority and technical credibility alike, building alignment across peer engineering, Product, Design, Security, Operations, Sales, and Customer Success organizations
- Strong judgment in balancing long-term architecture with pragmatic execution, customer impact, engineering velocity, and business priorities
- Experience mentoring senior engineers, raising engineering standards, and building reusable patterns that create leverage across teams
- Experience with AI-powered products, automation platforms, AI-assisted workflows, or agentic systems
- Ability to reason about AI-assisted enterprise workflows, including data quality, workflow correctness, evaluation, observability, safety controls, and human-in-the-loop review
- Experience with enterprise service management, IT operations, CMDB, discovery, service mapping, AIOps, observability, workflow automation, endpoint management, or operational intelligence
Desired Qualifications
- Experience working with large-scale enterprise customers, production systems, and complex migration or modernization efforts
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