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About the Role

This is a hands-on security engineering role focused on securing AI systems, acting as a trusted advisor to define and evolve AI security standards, patterns, and guardrails. The objective is to ensure security capabilities evolve with AI adoption and remain effective at enterprise scale.

Responsibilities

Act as security design authority for AI systems, leading threat modelling, architecture review, and risk assessment for agentic applications, the model gateway, Accio, Nexus, and any novel or high-risk AI initiative.
Define and evolve AI security standards, guardrails, governance controls, and secure-by-design patterns aligned with enterprise requirements and the firm’s risk appetite.
Design identity, entitlement, and secrets patterns for non-human identities, covering scoped permissions, credential lifetime, rotation, and least privilege across multi-hop requests.
Set the trust boundaries and data-egress controls for the AI estate, including what may reach external model providers.
Run adversarial testing and AI red teaming against models, prompts, agents, and tool chains.
Build detections, security analytics, and telemetry for AI-specific abuse and integrate them into the firm’s monitoring estate.
Support security incident response for AI systems, including triage, containment, forensics, and root cause analysis.
Own security testing in the AI delivery lifecycle, including static analysis, dependency and container scanning, secrets detection, and security gates in CI/CD.
Co-own the risk-based security gate for onboarding new AI products, model providers, versions, and platform features.
Conduct security due diligence and risk assessment of AI vendors, platforms, and models.
Decide which Copilot features are released and to whom, withholding capability until the required controls are evidenced.
Review solutions built by Forward Deployed Engineering and platforms built with Percepta to ensure security.
Set the guardrails for citizen developers and Copilot Studio makers.
Support Risk and Internal Audit with security evidence and exercise Infosec’s security-control approval and risk-acceptance position for AI.
Identify and deliver opportunities to apply AI and automation across security operations, engineering, assurance, and governance.
Define and report the KPIs, KRIs, dashboards, and reporting that demonstrate risk reduction, control effectiveness, and operational improvement.
Mentor security engineers on AI security and build AI literacy across Infosec.

Requirements

Strong cybersecurity experience across security engineering, application security, product security, cloud security, or security architecture, with a hands-on engineering background.
Hands-on experience assessing and securing GenAI, LLM, machine learning, agentic AI, and AI-enabled solutions throughout their lifecycle.
Proven ability to lead threat modelling, architecture reviews, and risk assessments for complex technology platforms and services.
Strong understanding of AI-specific threats, threat modelling methodologies, adversary frameworks, and risk assessment approaches.
Experience defining and evolving AI security standards, guardrails, governance controls, and secure-by-design patterns.
Experience securing AI agents, MCP integrations, permissions, non-human identities, autonomous workflows, and AI platform integrations.
Cloud security depth, ideally Azure — identity and access management, service principals and workload identity, secrets management, RBAC, network controls, and logging.
Experience securing application delivery, including secure SDLC, CI/CD controls, and code and dependency scanning.
Practical experience with AI and LLM systems — prompt engineering, retrieval-augmented generation, function calling, agent-based tools.
Proven ability to build and deploy automation using code, APIs, scripting, orchestration platforms, or low-code technologies such as Python, workflow engines, or SOAR.
Metrics-driven mindset, with experience defining KPIs, KRIs, dashboards, and reporting to demonstrate risk reduction, control effectiveness, and operational improvement.
Strong stakeholder engagement and influencing skills, with the ability to translate technical risk into business impact, pragmatic controls, and informed risk decisions.
Independence to hold a security position under delivery pressure.
Familiarity with AI security and governance frameworks including NIST AI RMF, the OWASP Top 10 for LLM applications, MITRE ATLAS, ISO/IEC 42001, and the security provisions of the EU AI Act.
AI red teaming, adversarial testing, adversarial machine learning, model validation, or offensive security assessments applied to models and tool chains.
Experience securing enterprise AI platforms, model gateways, AI development environments, and AI engineering ecosystems.
Knowledge of AI security posture management, runtime protection, model monitoring, and AI governance tooling.
Knowledge of identity security, including IAM, PAM, identity governance, privileged access management, non-human identities, and workload identities.
Experience applying AI and automation to vulnerability management, detection engineering, threat detection, or security operations at scale.
Knowledge of security analytics, monitoring, and detection capabilities for AI systems and supporting infrastructure.
Understanding of privacy, data governance, regulatory, and responsible AI considerations.
Securing agentic workflows, including scoped permissions, approval patterns, and guarding against configuration drift caused by AI assistants.
Third-party or model supply-chain risk assessment.
Financial services or asset management experience.
A certification such as CISSP, GIAC, OSCP, or a cloud security qualification.
Willingness to adhere to the provisions of our Investment Advisory Code of Ethics related to personal securities activities and other disclosure and certification requirements.
Understanding of the regulatory obligations of the firm, and abide by the regulated entity requirements and JHI policies applicable for your role.

Skills

Cybersecurity
Security Engineering
Application Security
Product Security
Cloud Security
Security Architecture
GenAI
LLM
Machine Learning
Agentic AI
AI-enabled solutions
Threat Modelling
Risk Assessment
STRIDE
PASTA
MITRE ATT&CK
MITRE ATLAS
Identity and Access Management (IAM)
Service Principals
Workload Identity
Secrets Management
Role-Based Access Control (RBAC)
Network Controls
Logging
Secure Software Development Lifecycle (SDLC)
Continuous Integration/Continuous Deployment (CI/CD)
Code Scanning
Dependency Scanning
Prompt Engineering
Retrieval-Augmented Generation (RAG)
Function Calling
Agent-based Tools
Python
Workflow Engines
Security Orchestration, Automation, and Response (SOAR)
API Integration
Scripting
KPIs
KRIs
Dashboards
Reporting
Stakeholder Engagement
Influencing Skills
NIST AI RMF
OWASP Top 10 for LLM applications
ISO/IEC 42001
EU AI Act
AI Red Teaming
Adversarial Testing
Adversarial Machine Learning
Model Validation
Offensive Security Assessments
AI Security Posture Management
Runtime Protection
Model Monitoring
AI Governance Tooling
Privileged Access Management (PAM)
Identity Governance
Vulnerability Management
Detection Engineering
Threat Detection
Security Operations
Security Analytics
Privacy
Data Governance
Responsible AI
Microsoft Purview
Data Loss Prevention (DLP)
Data Classification
Microsoft 365
Agentic Workflows
Configuration Drift
Model Supply-Chain Risk Assessment
Financial Services
Asset Management
CISSP
GIAC
OSCP
Cloud Security Qualification

Location

Hybrid

Work Type

Hybrid working

Experience Level

Individual-contributor role
Security design authority
Mentors security engineers

Salary/Compensations

Position may be eligible to receive an annual discretionary bonus award from the profit pool.

Benefits

Competitive compensation
Pension/retirement plans
Various health, wellbeing and lifestyle benefits
Hybrid working and reasonable accommodations
Generous Holiday policies
Excellent Health and Wellbeing benefits including corporate membership to Wellhub
Paid volunteer time
Support to grow through professional development courses, tuition/qualification reimbursement and more
Maternal/paternal leave benefits and family services
All employee events including networking opportunities and social activities
Lunch allowance for use within our subsidized onsite canteen

About the Company

A career at Janus Henderson is more than a job, it’s about investing in a brighter future together.
Our Mission at Janus Henderson is to help clients define and achieve superior financial outcomes through differentiated insights, disciplined investments, and world-class service.
Our Values are key to driving our success, and are at the heart of everything we do: Clients Come First - Always | Execution Supersedes Intention | Together We Win | Diversity Improves Results | Truth Builds Trust
Janus Henderson is undertaking a firm-wide AI transformation to become the most technologically sophisticated asset manager in the industry.
Our AI capability sits in a single centralised function under the Head of AI, and AI Technology builds and runs it.
This role sits in Information Security and reports to the Head of Security Engineering, while your day-to-day work is directed by AI Technology and prioritised against their roadmap.
Security policy, security architecture approval, and security risk acceptance stay with Infosec, and you are the person who exercises them for AI — close enough to the engineering to be useful, independent enough to say no.
Janus Henderson Investors is committed to an inclusive and supportive environment.
We believe diversity improves results and we welcome applications from candidates from all backgrounds.

Equal Opportunity

Janus Henderson Investors is an equal opportunity employer.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.