Staff Machine Learning Engineer, SecureAI
Core
Architecting and driving features for a unified control plane to establish the premier Identity Security Fabric for the agentic era, replacing static rules with dynamic AI security mechanisms.
Role type
Staff Machine Learning Engineer (Generative AI & Security)
Builds
Real-time threat inspection, agent intent evaluation, behavioral analysis, and scalable ML/GenAI systems integrating retrieval, inference, and evaluation pipelines.
Domain
Cybersecurity, Digital Identity, Generative AI, Agentic Systems
Deliverable
production ML models
Required skills
Python, Applied Machine Learning, Generative AI platforms (AWS Bedrock, OpenAI, Anthropic), RAG, Embeddings, Vector Search, Zero-shot classification, LLM reasoning, Prompt parsing, LiteLLM, LangGraph, LangChain, LlamaIndex, MCP, ML frameworks (PyTorch, TensorFlow), Workflow orchestration (Airflow), Evaluation metrics design
Preferred skills
Identity/authentication/security product integration, Ethical AI, Model risk, Compliance frameworks, Synthetic data generation, LLM-as-a-judge methods
Technologies
AWS Bedrock, OpenAI, Anthropic, LiteLLM, LangGraph, LangChain, LlamaIndex, MCP, FastAPI, PyTorch, TensorFlow, Spark ML, Airflow, Cedar
Responsibilities
Implement intent-based enforcement to verify agent runtime requests; Apply LLM reasoning and prompt parsing to interpret prompts and tool payloads; Integrate low-latency inference engines into API gateways; Design confidence-scored decision engines for policy frameworks; Establish evaluation benchmarks and guardrails against prompt injection; Architect scalable ML and GenAI systems; Optimize prompting, context retrieval, and RAG workflows; Build automated evaluation pipelines for model quality and safety.
Seniority
Staff, hands-on IC with strategic architecture