Senior AI Cyber Security Engineer

About this role

Company Overview ImmunityBio is a vertically integrated commercial stage biotechnology company developing next-generation therapies that bolster the natural immune system to defeat cancers and infectious diseases. The Company’s range of immunotherapy and cell therapy platforms, alone and together, act to drive and sustain an immune response with the goal of creating durable and safe protection against disease. Designated an FDA Breakthrough Therapy, ANKTIVA is the first FDA-approved immunotherapy for non-muscle invasive bladder cancer CIS that activates NK cells, T cells, and memory T cells for a long-duration response. The Company is applying its science and platforms to treating cancers, including the development of potential cancer vaccines, as well as developing immunotherapies and cell therapies that we believe sharply reduce or eliminate the need for standard high-dose chemotherapy. These platforms and their associated product candidates are designed to be more effective, accessible, and easily administered than current standards of care in oncology and infectious diseases.

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) is preferred. • Experience with security logging/observability stacks (SIEM, data lakes, security analytics) and building detections for AI‑related threats is preferred. • Relevant certifications e.g., cloud security, offensive security, or AI‑focused credentials is preferred.

Knowledge, Skills, & Abilities • Strong understanding of modern cloud platforms (AWS, Azure, or GCP) and container/orchestration technologies (Docker, Kubernetes) as they apply to AI workloads. • Solid knowledge of common AI/ML threat scenarios: data poisoning, model theft/exfiltration, adversarial examples, model inversion, prompt injection, jailbre

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