Sr. Manager, AI Software Engineering

SentinelOne

3d•$200,000 - $275,000

About The Position

As a Senior Manager, AI Software Engineering, you will be tasked with managing and scaling AI Engineering teams responsible for delivering production-grade AI systems and customer-facing AI capabilities. Sitting within the P&T organization, you will play a key part in translating AI strategy into reliable, scalable software and platform outcomes. You will lead engineers working on AI-powered product capabilities, platform services, and supporting infrastructure while partnering closely with Product, Architecture, Security, Data, and other Engineering leaders to deliver high-impact AI initiatives with quality, speed, and operational rigor.

Requirements

8 or more years of experience in software engineering, machine learning engineering, or closely related technical fields.
3 or more years of experience leading engineering teams, including managing managers and/or senior engineers in a high-growth environment.
Proven track record of shipping production-grade software, AI, or data products at scale.
Strong technical depth in distributed systems, cloud-native services, and modern software engineering practices.
Experience building or operating AI and ML systems, including model integration, evaluation, deployment, monitoring, and lifecycle management.
Familiarity with MLOps and platform capabilities required to support reliable AI product delivery.
Strong understanding of engineering quality, security, observability, and operational excellence practices.
Experience partnering effectively with Product, Design, Security, Data, and Infrastructure teams.
Excellent communication skills and the ability to align senior stakeholders around priorities, tradeoffs, and execution plans.
Demonstrated success hiring and developing high-performing engineering teams.

Nice To Haves

Experience leading teams that build AI-powered product features in cybersecurity, enterprise software, or data-intensive environments is preferred.
Experience with large-scale event processing, real-time systems, or detection and analytics platforms is preferred.
Hands-on familiarity with cloud platforms such as AWS or GCP, as well as Kubernetes, Docker, and modern CI/CD practices is preferred.
Experience with LLM-powered applications, agentic workflows, retrieval systems, or applied AI platform services is preferred.
Background in endpoint security, cloud security, SIEM, or adjacent security domains is preferred.

Responsibilities

Lead and grow one or more AI Engineering teams focused on delivering production AI capabilities and platform services.
Drive execution for strategic AI initiatives across the P&T organization, including customer-facing features, internal AI platform capabilities, and supporting engineering systems.
Partner with Product Management and cross-functional engineering leaders to translate roadmap priorities into clear technical plans, delivery milestones, and team outcomes.
Establish strong engineering management practices across planning, execution, quality, incident response, observability, and continuous improvement.
Mentor engineering managers and senior individual contributors while building a culture of accountability, innovation, and operational excellence.
Help define and enforce best practices for AI system development, MLOps, service reliability, security, and performance.
Support architecture and design decisions for scalable, low-latency, highly available AI systems and services.
Recruit, develop, and retain top engineering talent across AI, software, and platform domains.
Improve collaboration across globally distributed teams and ensure effective delivery across organizational boundaries.
Contribute to organization design, capacity planning, and quarterly and annual planning aligned to P&T and AI goals.
Operate as a delivery-focused engineering leader who balances innovation with reliability; raise the bar on execution discipline, technical quality, and cross-functional collaboration; build healthy teams with clear accountability, strong coaching, and high trust; make pragmatic decisions, surface risks early, and drive issues to resolution; and foster a culture that values customer impact, learning velocity, and engineering excellence.