GenAI Security Platform Architect

Bachelor's degree in Computer Science, Engineering, Information Security, or equivalent experience. Minimum 8 years in Cybersecurity with 3 years focused on securing AI/ML systems or GenAI applications in production. CISSP certification required Demonstrated deep technical experience designing secure architectures for: ML pipelines and MLOps platforms (data ingestion, feature stores, training, model registry, deployment, monitoring). GenAI workloads (LLM APIs, fine-tuning, RAG, vector databases, agent frameworks). Cloud-native environments (containers/Kubernetes, serverless, service mesh, VPC/network security). Strong knowledge of AI-specific threats and mitigations: data poisoning, model inversion/membership inference, model theft/IP protection, adversarial examples, prompt injection/jailbreaks, exfiltration via outputs, and LLM supply chain risks. Practical familiarity with security frameworks and standards: NIST AI RMF, OWASP Top 10 (including LLM apps), MITRE ATT&CK and ATLAS, or similar. Hands-on experience implementing: Identity and access controls for AI services (service principals, fine-grained IAM, token and key management). Secrets management (Vault, KMS/Key Vault/Cloud KMS/HSM), encryption-in-transit/at-rest, data tokenization, DLP. Monitoring/logging for AI systems (model telemetry, prompt/response logging with privacy controls, drift/anomaly detection). Demonstrated ability to quickly learn and build expertise in diverse and emerging technologies and new architectural concepts and principles Strong influencing and consensus building skills, and the adaptability to respond to change quickly Strong communications skills, both written and verbal Ability to effectively collaborate with all levels of the organization with diverse backgrounds Strong desire to drive change, and ability to adapt to change quickly Excellent communication skills; ability to influence architecture and risk decisions across engineering, product, and executive stakeholders. Experience with enterprise GenAI platforms and tools: MLOps: SageMaker, Vertex AI, Cortex, AWS ML, Azure ML, MLflow, KServe/Seldon/Triton, Feast/Tecton HuggingFace. LLM/GenAI: Azure OpenAI, AWS Bedrock, OpenAI, LangChain/LangGraph/Semantic Kernel, vector DBs (Pinecone, Weaviate, FAISS/Chroma), guardrails/middleware (e.g., Llama Guard, Lakera, Protect AI, Robust Intelligence, HiddenLayer), GitHub Copilot, GitHub Copilot Coding Agent, Devin.ai, M365 Copilot, Copilot Web. Observability: Prometheus/Grafana, ELK/Opensearch, Splunk, Cribl; AI eval frameworks and red-team tooling. Advanced degree (MS/PhD) in Security, ML/AI, or related field is a plus. Automate-by-default: codify controls in pipelines and platforms rather than relying on manual gates.