Security Engineer Agentic AI Security

The team is hiring a hands-on security engineer to build and security-test a realistic clinical agentic AI system.

The target system is a clinical assistant that retrieves and reasons over synthetic patient records and clinical guidelines, drafts clinical documentation, and answers clinician queries. Human confirmation will be required before any action that writes back or sends information.

The engineer will build the prototype and conduct a structured security assessment covering the key attack surfaces of agentic AI, with a focus on practical security assurance for healthcare deployment.

What the role involves

Build the clinical agent

Implement a clinical agent using LangGraph , with MCP , RAG and synthetic patient records

Implement basic access controls, data protection and human-in-the-loop action gating

Document the architecture, trust boundaries and security assumptions

Threat model and red-team

Develop a threat model covering the agent, tools, memory and data flows

Conduct structured security testing covering: indirect prompt injection malicious/poisoned MCP tools memory poisoning action-gate bypass and unauthorised tool use sensitive-data exfiltration code-execution risks, where applicable

Adapt existing agentic-AI security benchmarks and tools where appropriate

Findings and mitigation

Document security findings, severity and attack paths

Recommend and, where feasible, validate practical mitigations

Provide deployment recommendations for secure use of agentic AI in clinical settings

Key Deliverables

Working clinical agent security testbed (LangGraph + MCP + RAG + synthetic data)

Threat model and documented attack surface

Reusable red-team/security evaluation harness

Security assessment report with findings, mitigations and deployment recommendations

Practical security testing guidelines for future healthcare agentic-AI systems