Role Overview

FNZ is seeking an AI Security Specialist to shape, build, and operationalise AI-enabled solutions within Security Technology Operations. This is a hands-on technical specialist role focused on enabling practical, supportable AI use cases.

The successful candidate will combine strong software and platform engineering skills with demonstrable AI engineering experience. Providing the ability to work across security functions and to provide ‘front door’ consultancy support to technology and architecture colleagues whilst interacting with colleagues in Security Technology and Operations.

The role is delivery-focused: building useful AI capabilities, integrating them into real workflows, and ensuring they can be operated effectively in production.

This role works closely with FNZ's AI Governance and Security Architecture teams. It is responsible for leading AI initiatives within Security Technology Operations in line with enterprise standards and approved architectural patterns.

Core Responsibilities

AI Use Case Identification & Delivery
Lead the discovery, prioritisation, and delivery of AI-enabled use cases across Security Technology Operations. This includes working with Engineering, SOC, Threat Intelligence, and IAM teams to identify where AI can improve analyst effectiveness, automation, decision support, and operational efficiency. Responsibilities include:

• Identifying high-value security AI use cases and rejecting poor-fit opportunities

• Converting operational problems into clear technical solution designs and backlogs

• Defining measurable outcomes, success criteria, and adoption plans

• Ensuring solutions are grounded in real workflows rather than isolated proofs of concept

AI Solution Engineering & Operationalization
Design, build, and operationalize AI solutions that can run reliably in production. This includes both hands-on engineering and technical direction across the solution lifecycle. Responsibilities include:

• Building AI-enabled workflows, services, and assistant capabilities on Azure and related Microsoft platforms

• Applying appropriate patterns such as RAG/grounded retrieval, summarisation, classification, extraction, orchestration, and human-in-the-loop controls

• Integrating AI solutions with security tooling, knowledge sources and internal systems

• Establishing evaluation, testing, observability, and support patterns for AI solutions

• Managing prompt, workflow, and solution changes with engineering discipline

Cross-Functional Partnership
Work closely with partner teams to ensure AI solutions are usable, safe, and aligned with enterprise controls. Responsibilities include:

• Collaborating with AI Governance on acceptable use, controls, and deployment guardrails

• Working with Security Architecture on approved patterns, integrations, data flows, and risk decisions

• Partnering with Security Engineering, SOC, Threat Intelligence, and IAM leads on use case design and adoption

• Feeding operational lessons and design constraints back into architecture and governance discussions

Technical Leadership
Provide technical leadership for applied AI delivery within Security Technology Operations. Responsibilities include:

• Acting as the senior technical lead for AI solution design and delivery

• Mentoring engineers and guiding teams on solution design, trade-offs, and delivery practices

• Challenging weak use cases, poor assumptions, and fragile designs

Platform & Capability Improvement
Continuously improve FNZ's ability to deliver AI solutions in security operations and engineering. Responsibilities include:

• Driving reusable patterns, templates, and integration approaches for security AI delivery

• Improving telemetry, evaluation, and reporting for AI solution performance and value

• Identifying opportunities to reduce manual effort, improve investigation speed, and strengthen engineering efficiency

• Contributing to longer-term AI capability development within Security Technology Operations

Working Pattern

The team supports global security operations and engineering functions across multiple regions. Core hours will align primarily with APAC and EMEA collaboration, with regular interaction across international teams. Occasional out-of-hours work may be required to support critical incidents, production changes, or key delivery milestones.

Required Experience

Candidates should demonstrate strong hands-on experience with demonstrable AI delivery experience. Typical background includes:

• 5+ years in security operations, cyber security platform engineering or related technical roles

• Demonstrable experience delivering AI/ML or generative AI solutions beyond proof-of-concept stage

• Strong experience building solutions in enterprise environments with operational, security, and governance constraints

• Proven ability to work across multiple stakeholder groups to shape and deliver technical solutions

• Experience operating in distributed global teams

Technical Experience

Strong hands-on experience across several of the following areas is expected:

• Azure AI services, ideally including Azure AI Foundry and/or Azure OpenAI

• Designing and implementing RAG/grounded AI solutions against enterprise knowledge sources

• Building AI patterns such as summarisation, classification, extraction, search, orchestration, and analyst-assist workflows

• API-based integrations and service-oriented solution design

• Evaluation, regression testing, observability, and operational monitoring for AI solutions

• Identity-aware and security-conscious design for enterprise AI integration

• Working with cloud-native services, automation, and CI/CD practices

Candidates should also demonstrate enough security awareness to build responsibly within enterprise guardrails, including sensitivity to data handling, access control, prompt/output risk, and auditability.

Nice to Have

Experience in the following areas is beneficial:

• Microsoft Copilot Studio and/or Microsoft 365-connected agent solutions

• Security operations, SOC, threat intelligence, IAM, or security engineering domain experience

• SIEM, SOAR, case management, or security workflow automation integrations

• Exposure to Purview, DLP, Entra ID, or related Microsoft security and governance controls

• Experience in regulated or high-assurance environments

• Infrastructure-as-code, DevOps, or platform engineering practices

What Success Looks Like

The successful candidate will:

• Deliver AI-enabled solutions that improve real security operations and engineering outcomes

• Build credible, supportable capabilities rather than isolated demos

• Improve efficiency, analyst experience, and decision support across security teams

• Strengthen collaboration between delivery teams, Architecture, and AI Governance

• Contribute to the long-term evolution of FNZ's AI capability in security operations and engineering

Why This Role Matters

Security Technology Operations needs practical AI capability that is useful, supportable, and aligned with enterprise controls. This role is central to ensuring FNZ can apply AI where it adds genuine value across security operations and engineering, while maintaining the operational discipline, security awareness, and cross-functional collaboration required in a regulated environment.