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The Role GM’s Cybersecurity Team safeguards the company’s global information assets, networks, and infrastructure. Our mission is to proactively defend GM against evolving cyber threats through strategic leadership, technical excellence, and innovative risk management. We seek cybersecurity professionals with advanced expertise, capable of driving enterprise security initiatives and influencing organizational resilience. As a Staff Security Software Engineer on GM’s Security Operations Engineering team , you will define the technical strategy and architecture for enterprise-scale security integrations and AI-driven automation. You’ll set standards for how data flows across our security stack, create platform capabilities that multiple teams build upon, and influence executive roadmap decisions. You operate with high autonomy, shape organizational practices, and deliver platform-level outcomes.
Job Responsibility:
Set the reference architecture for security data integration and AI orchestration (agents, policy-guard railed workflows, governance)
Lead cross-org programs that unify SIEM/EDR/IAM/SSPM/CSPM/ITSM/cloud data models and establish single sources of truth
Operationalize AI at scale with safety, privacy, and governance—including data retention, PII controls, model routing, evaluation, and fallback strategies
Drive cost/performance optimization (throughput, latency, storage tiering, vector index strategies) for high-volume security telemetry
Influence vendor strategy and negotiate integration roadmaps
guide build-vs-buy decisions and multi-year investments
Mentor/coach Staff/Senior engineers
build a culture of design excellence, pragmatic risk management, and measurable outcomes
Communicate upward with crisp executive narratives, metrics, and business impact framing
Requirements:
8+ years in software engineering with a focus on distributed systems, security integrations, and data platforms
Deep expertise building event-driven, horizontally scalable services and contract-first APIs
Track record productizing AI in security workflows (multi-agent patterns, RAG at scale, evaluation harnesses, guardrails, red-teaming)
Cloud architecture depth (Azure/AWS/GCP), including networking, Kubernetes, service meshes, observability stacks, and IaC at scale
Data platform expertise: streaming (Kafka/Event Hub/PubSub), vector/search (pgvector/FAISS/Pinecone), schema/versioning, governance/lineage
Demonstrated org-wide influence: authored standards, drove cross-team adoption, led multi-quarter programs to successful outcomes
Exceptional communication with executives
ability to frame risk, ROI, and tradeoffs succinctly
Nice to have:
Led creation of shared security data model or knowledge graph spanning multiple tools and clouds
Experience with AI safety/privacy: policy engines, data minimization, content filtering, evaluation metrics
Vendor ecosystem leadership: co-developing integrations, shaping roadmaps, or contributing to standards (e.g., STIX/TAXII)