Summary
✨ AI‑Generated
A global financial organization is expanding its AI security capabilities and seeks an engineer to secure production AI systems, cloud platforms, and AI-driven workflows. The role combines security engineering, threat analysis, and modern AI risk management.
Highlights
High-impact security role focused on protecting advanced AI systems, designing security controls, and addressing emerging technology risks.
Description
[Up to c.
$300k Base Salary + Discretionary Bonus | Office-Led Working - Likely 4 Days in Office]
Role Overview
A leading global investment firm is building out its AI security capability as GenAI becomes more deeply embedded across internal platforms, engineering workflows and business-critical technology.
This is a hands-on engineering role focused on securing production AI systems, agentic workflows, internal tools and cloud-native platforms across a high-calibre technology environment...
Key Responsibilities
Design and build security controls for internal GenAI applications, APIs, model usage patterns and platform integrationsSecure agentic AI, tool-calling and connector-based workflows, including MCP-style integrations and privileged system accessLead technical threat modelling across prompt injection, jailbreaks, data leakage, tool abuse, model misuse and AI supply-chain riskDefine secure reference patterns for cloud-native and hybrid GenAI workloads, including secrets, network boundaries and service isolationBuild monitoring and detection logic for unusual AI behaviour, unsafe outputs, suspicious tool activity and potential data exposureSupport response and remediation for incidents involving AI-enabled applications, internal platforms or sensitive informationTranslate AI security requirements into practical engineering controls, evidence, testing and audit-ready documentationAct as a technical AI security partner to engineering, infrastructure, MLOps, product, legal, compliance and business stakeholders
What You’ll Bring…
5+ years of software engineering, product security, application security or security engineering experience, with strong hands-on coding in Python, Go, Java or similarPractical experience with AI/ML or GenAI technologies, ideally including LLM applications, RAG, agents, tool-calling, model APIs or AI platform infrastructureStrong understanding of AI security risks, including prompt injection, unsafe tool execution, data exfiltration, jailbreaks, training data leakage and supply-chain exposureExperience building, deploying or securing containerised services using KubernetesAbility to design and deliver production-grade security controls without slowing down engineering deliveryStrong threat-modelling capability across modern software, cloud, API, data and AI-enabled systemsExperience working with CI/CD, infrastructure pipelines, DevOps, MLOps or platform engineering teamsClear communication style, with the ability to influence technical and non-technical stakeholders in a high-performance environment(Preferred) Financial services, hedge fund, trading, fintech or other highly regulated technology environment experience(Preferred) Experience with MCP, LangChain, LlamaIndex, Bedrock, OpenAI/Azure OpenAI, Vertex AI, vector databases or AI gateway/guardrail tooling(Preferred) Experience building detection, observability or incident-response workflows for AI, cloud or application security events
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