Senior AI Cyber Security Engineer

Benefits

Additional Information

Company Overview ImmunityBio, Inc. (NASDAQ: IBRX) is a commercial-stage biotechnology company developing cell and immunotherapy products that are designed to help strengthen each patient's natural immune system, potentially enabling it to outsmart the disease and eliminate cancerous or infected cells. We envision a day when we no longer fear cancer, but can conquer it, thanks to the biological wonder that is the human immune system. Our scientists are working to develop novel therapies that harness that inherent power by amplifying both branches of the immune system, attacking cancerous or infected cells today while building immunological memory for tomorrow. The goal: to reprogram the patient's immune system and treat the host rather than just the disease. Why ImmunityBio? - ImmunityBio is developing cutting-edge technology with the goal to transform the lives of patients with cancer and develop next-generation therapies and vaccines that complement, harness and amplify the immune system to defeat cancers and infectious diseases. - Opportunity to join a publicly traded biopharmaceutical company with headquarters in Southern California. - Work with a collaborative team with the ability to work across different areas of the company. - Ability to join a growing company with professional development opportunities. Position Summary The Senior AI Cybersecurity Engineer is responsible for securing AI/ML systems end‑to‑end: from data pipelines and model training to deployment, monitoring, and abuse prevention. This role combines deep security engineering expertise with practical experience building or protecting machine learning and generative AI workloads. You will partner with data science, platform, product, and security teams to design secure architectures for AI services, conduct threat modeling for AI/ML use cases, detect and respond to AI‑driven and AI‑targeting attacks, and help define secure development and governance practices for AI across the organization. Essential Functions Design and implement security controls for AI/ML platforms, including model training environments, inference services, data pipelines, and feature stores. Conduct threat modeling for AI systems, including model theft, data poisoning, prompt injection, model inversion, and abuse/misuse scenarios. Build and maintain security tooling and automation to detect and prevent AI specific attacks (e.g., adversarial inputs, prompt injection chains, anomalous usage patterns). Collaborate with data scientists and ML engineers to integrate security into the AI development lifecycle (secure coding, model validation, testing and red teaming for AI behaviors). Evaluate and harden integrations with third party AI providers (LLM APIs, vector databases, orchestration frameworks, agents), including authentication, authorization, data handling, and logging. Collaborate with cloud/platform teams to ensure AI infrastructure (Kubernetes, GPU clusters, model registries, CI/CD) follows security best practices and compliance requirements. Define and implement monitoring for AI systems, including abuse detection, drift and anomaly alerts, model access patterns, and security relevant telemetry. Partner with incident response teams on investigations involving AI systems, including analyzing logs, traffic, model behavior, and potential data/model compromise. Contribute to policies, standards, and guardrails for responsible and secure use of AI internally (e.g., data classification rules for training inputs and prompts, allowed use cases, evaluation requirements). Provide technical guidance and mentorship to other engineers on AI security concepts, threats, and secure design patterns. Stay current on emerging AI threats, vulnerabilities, frameworks, and regulatory trends, and translate them into practical recommendations for the organization. Create, edit and adhere to Standard Operating Procedures (SOPs), process improvements, and standardization of templates. Performs ad-hoc and cross-functional duties and/or projects as assigned to support business needs and provide developmental opportunities. Education & Experience Bachelor's Degree with 8+ years of relevant experience is required; OR High school Diploma or equivalent with at least 12 + years of relevant experience is required. 5+ years of hands-on security engineering experience (application, product, cloud, or infrastructure), including designing and implementing security controls in production environments is required. Practical experience with AI/ML systems (e.g., working with ML pipelines, LLM applications, vector search, or MLOps platforms), whether as a security engineer or as an engineer collaborating closely with ML teams is required. Experience implementing authentication/authorization, secrets management, network segmentation, and secure CI/CD for services and APIs is required. Experience securing LLM and generative AI applications (e.g., RAG architectures, AI agents, chatbots, code assistants)