Sr. Engineering Manager, Platform API - Sensor Foundations (Hybrid)

CrowdStrike•New York City, NY

1d•$160,000 - $250,000•Hybrid

About The Position

CrowdStrike is hiring a Senior Engineering Manager to lead the Platform API team, which builds cross-platform APIs and abstractions for the Falcon sensor across Windows, Linux, and macOS. The team owns foundational components such as threading, file I/O, hashing, work queues, and memory management. Its work provides a consistent interface that separates sensor feature development from operating-system-specific implementation and is relied on by engineering teams throughout the sensor organization. The manager will own the team’s technical roadmap, strategy, and execution, including a multi-year effort to consolidate platform behavior into a unified, well-tested foundation. A major initiative is a shared on-sensor machine-learning inference runtime, with a stable C API and an isolated out-of-process service that can use hardware-accelerated backends on each platform. The manager will guide this runtime from design through production delivery, make decisions about API design and long-term compatibility, and build partnerships that support adoption across the sensor organization. This is a hands-on technical leadership role. The manager is not expected to write code on the critical path, but must understand the team’s API contracts, compatibility constraints, and cross-platform systems well enough to contribute to reviews, troubleshoot, guide design, and represent the team in cross-functional discussions. The role includes hiring and developing engineers, managing workload and resourcing, maintaining quality, handling support escalations, and communicating roadmaps and progress to senior leadership. The role is hybrid and requires on-site work two days per week at one of the posted locations. Occasional travel for team offsites and in-person meetings is required. The U.S. base salary range is $160,000–$250,000 per year, with eligibility for bonuses and equity grants.

Requirements

Proven experience managing software engineering teams, built on a strong foundation as a software developer.
Hands-on low-level systems software experience, with deep expertise in C and/or C++ in user-mode and kernel-mode environments.
Strong grounding in API and interface design, including interface clarity, ABI stability, backward compatibility, and the downstream impact of breaking changes in a large codebase.
Cross-platform experience across Windows, Linux, and macOS, including reasoning about portability, behavioral consistency, and platform-specific constraints.
Familiarity with out-of-process architecture patterns, including sandboxed service isolation, inter-process communication, and performance tradeoffs across process boundaries.
Experience owning production software at scale and understanding the impact of correctness regressions in software that runs continuously on customer endpoints.
Strong design and problem-solving skills and commitment to engineering excellence, quality, security, and performance.
Demonstrated success mentoring, coaching, and developing engineers.
Experience leading distributed teams while maintaining trust, velocity, and clarity.
Strong cross-functional collaboration skills and a track record of building credibility and influence across engineering, product, and program management.
Clear, direct communication with individual contributors through executive leadership.
Intellectual curiosity and commitment to deeply understanding systems before changing them.
Ability and willingness to travel occasionally for team offsites and in-person meetings.
Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency, and drive business outcomes.

Nice To Haves

Background in endpoint security, EDR, kernel-level software, or sensor platform engineering.
Experience designing or maintaining cross-platform API layers used by multiple teams in a large C/C++ codebase.
Experience building or leading teams that develop on-device ML inference infrastructure, including running machine-learning models and small language models on resource-constrained endpoints while balancing model size, latency, and resource consumption.
Experience with hardware-accelerated inference across GPU, NPU, and Apple Neural Engine, including hardware capability detection, backend selection, and graceful CPU fallback.
Familiarity with model execution frameworks such as ONNX Runtime, OpenVINO, or Core ML, including runtime versioning and static versus dynamic linking tradeoffs.
Experience designing out-of-process inference pipelines, including sandboxing for resource isolation and fault containment, low-latency IPC for model inputs and outputs, and telemetry for inference performance and hardware utilization.
Understanding of model lifecycle management at fleet scale, including staging, versioning, and silent validation before production rollout, particularly for SLM and LLM workloads.
Experience designing cross-language integration surfaces, such as C APIs consumed from Rust, Swift, and C++.
Experience establishing API governance through tooling such as lint rules, automated policy checks, and structured feedback loops with consuming teams.
Experience leading teams through significant growth or expanding scope.
Prior work in environments where reliability is non-negotiable at massive fleet scale.

Responsibilities

Set architectural direction for cross-platform API components, including threading, file I/O, hashing, work queues, and memory management.
Lead architecture and delivery of the centralized on-sensor machine-learning inference runtime, including C API design, ABI stability, cross-language use, out-of-process execution and sandboxing, and backend selection and versioning across platforms.
Make design decisions about shared versus platform-specific implementations, in-process versus out-of-process execution, and kernel-mode and user-mode constraints.
Drive adoption of platform APIs through linting, automated code review, and clear usage guidance.
Participate in design and code reviews and maintain a deep understanding of API contracts, compatibility constraints, and failure modes.
Hire, coach, and develop engineers; lead recruitment from initial contact through onboarding.
Build team cohesion, address interpersonal friction, and create an environment where engineers can do their best work.
Manage team resourcing and workload, adapt to changing priorities, and determine when work should be deferred.
Own the quality of shipped components, manage support escalations, and build working relationships with platform and partner teams.
Improve end-to-end testing and validation for components with strict correctness and compatibility needs, including tooling to validate against the platform without building the full sensor.
Build a data-driven roadmap using performance telemetry and defect trends, and communicate investment needs and progress to senior leadership.
Occasionally travel for team offsites and in-person meetings.
Use AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency, and drive business outcomes.

Benefits

Market-leading compensation and equity awards.
Comprehensive physical and mental wellness programs.
Competitive vacation and holidays.
Paid parental and adoption leaves.
Professional development opportunities for all employees, regardless of level or role.
Employee Networks, geographic neighborhood groups, and volunteer opportunities.
Office amenities.
Eligibility for bonuses and equity grants.
Health insurance.
401(k).
Paid time off.