About the role:
The GenAI Platform team builds the core building blocks that power CrowdStrike’s next generation of AI products—model inference, knowledge bases, agents/tools, guardrails, cost management, and the SDLC around AI artifacts (evaluation, benchmarking, versioning, deploy). This work is pivotal to the company’s AI journey and a major bet on the path to CrowdStrike’s $10B ARR ambition.
We look for an exceptionally strong, hands‑on manager who leads experienced engineers, sets a high technical bar, and jumps in to design and code when that unblocks the team. You operate in one‑week sprints with a “you build it, you run it” ownership model to ship value fast without breaking trust.
You partner very closely with the Charlotte AI team, with our data scientists, and with other engineering and product teams. You also engage ProdSec, InfoSec, Legal, and Privacy to deliver secure, compliant, enterprise‑grade AI capabilities.
What you’ll do:
Lead the core GenAI Platform team: own planning and execution for a significant slice of the platform; grow and coach a high‑caliber group of cloud/backend engineers and an SDET
Provide technical oversight: review designs, define architecture and APIs, contribute code and tests when needed to unblock progress, and hold the line on engineering excellence
Act as a product manager for selected platform capabilities: understand internal customer needs across partner teams, translate business requirements into crisp problem statements, define success metrics, and drive prioritization and trade‑offs
Run core processes end‑to‑end: on‑call rotation (participate and coordinate), incident response and retrospectives, customer‑support triage, active bug management, quarterly retrospectives, performance reviews, and 1:1s
Drive production readiness and operational excellence: SLOs, dashboards, alerts, runbooks, staged rollouts/rollbacks, and cost awareness across services
Partner across the company: day‑to‑day collaboration with Charlotte AI, data scientists, and other platform services; engage ProdSec/InfoSec/Legal/Privacy when required to ship compliant, secure solutions
Shape the roadmap: co‑create a 6–12 month platform roadmap, align sequencing with engineering directors, and navigate ambiguity and shifting priorities while landing to timelines
Hire and develop talent: drive recruiting end‑to‑end—from first touch through onboarding—and foster a culture of innovation and continuous learning in a rapidly evolving GenAI space
What you’ll bring:
8+ years in software engineering and 2+ years as an engineering manager (exceptional tech/team leads with informal people‑leadership experience are considered)
Technical bar at senior‑engineer level: able to understand, drive, and design complex distributed systems; comfortable reading/writing code for reviews, prototypes, and unblocking work
Platform DNA: experience building and operating shared services or platforms used by many teams (multi‑tenant concerns, contracts/SDKs, permissions, usage controls)
Proven delivery at scale: shipped and operated large, real‑world systems at meaningful scale (e.g., high QPS/millions of requests per day or thousands of enterprise users) with strong on‑call and postmortem habits
Cloud‑native execution: containers/Kubernetes and at least one major cloud (AWS, GCP); pragmatic about reliability, latency, and cost
Cross‑functional leadership: effective partnership with product managers, program managers, SDETs, data scientists etc.; able to influence without authority and drive alignment
People‑first leadership: empowering, supportive, and empathetic style that brings the best out of experienced engineers—especially under fast pace and shifting priorities
Startup‑style resilience: bias for action, operate in ambiguity, make decisions with incomplete information, and land outcomes in a one‑week sprint cadence
Excellent written and verbal communication: clear framing of decisions, trade‑offs, and status to varied audiences
Experience working across multiple geographies and time zones; flexibility to accommodate meetings with partners across the globe
Nice‑to‑haves:
GenAI production exposure: LLM serving, RAG, guardrails/safety, evaluation frameworks, and cost/latency tuning in production environments
Familiarity with GenAI tooling frameworks used in production (e.g., LangChain, LlamaIndex, CrewAI, n8n etc.)
Understanding of cybersecurity domain knowledge and security operations
Security‑first mindset with experience meeting privacy/compliance requirements for enterprise systems
