Senior Manager, AI Software Engineering

📍 United States

USD 200,000-275,000 per year

SENIOR

✅ Remote

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 4 AWS @ 3 CI/CD @ 3 Communication @ 6 Distributed Systems @ 7 Docker @ 3 Engineering Management GCP @ 3 Hiring @ 6 Kubernetes @ 3 LLM @ 4 MLOps @ 3 Machine Learning @ 7 Observability @ 7 Security @ 7

Details

SentinelOne is seeking a Senior Manager, AI Software Engineering to manage and scale AI Engineering teams responsible for production-grade AI systems and customer-facing AI capabilities. Within the Product and Technology organization, this role will translate AI strategy into reliable, scalable software and platform outcomes. The role will lead engineers working on AI-powered product capabilities, platform services, and supporting infrastructure while partnering with Product, Architecture, Security, Data, and Engineering leaders.

Responsibilities

Lead and grow one or more AI Engineering teams focused on production AI capabilities and platform services.
Drive strategic AI initiatives across the Product and Technology organization, including customer-facing features, internal AI platform capabilities, and supporting engineering systems.
Partner with Product Management and engineering leaders to translate roadmap priorities into technical plans, delivery milestones, and team outcomes.
Establish engineering management practices covering 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.
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 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 with Product and Technology and AI goals.
Balance innovation with reliability, improve execution discipline and technical quality, surface risks early, and drive issues to resolution.

Requirements

At least 8 years of experience in software engineering, machine learning engineering, or closely related technical fields.
At least 3 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 machine learning systems, including model integration, evaluation, deployment, monitoring, and lifecycle management.
Familiarity with MLOps and platform capabilities that support reliable AI product delivery.
Strong understanding of engineering quality, security, observability, and operational excellence practices.
Experience partnering 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.
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.
Familiarity with AWS or GCP, 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.

Benefits

Restricted Stock Units and Employee Stock Purchase Plan.
Flexible time off, paid company holidays and sick time, gender-neutral parental leave, and grandparent leave.
Medical, dental, and vision coverage; 401(k) with company match; life and disability insurance; health and dependent care FSA; and other voluntary benefits.
Employee Assistance Program, prepaid legal services, pet insurance, Cancer Care program, and global business travel medical insurance.
Home office allowance and mobile phone reimbursement.
Wellness coach, wellness or gym reimbursement, fertility coverage, and adoption and surrogacy reimbursement.