Solutions Engineer, Financial Services

F5 F5 · Enterprise · Dublin, Ireland +1

Solutions Engineer focused on AI Runtime Security for Financial Services customers. This role involves driving sales motions, designing architectures, executing demos, navigating risk & compliance, and influencing the product roadmap for F5's AI security portfolio.

What you'd actually do

  1. Drive the Sales Motion: Partner with Enterprise Account Executives through the full sales cycle, from technical discovery and qualification through POCs, security reviews, and final technical close.
  2. Design Tailored Architectures: Create solution designs that map F5's AI security capabilities to complex FS environments, including hybrid cloud, legacy cores, and existing data platforms.
  3. Execute High-Impact Demos: Build and deliver compelling demonstrations of inference-layer protection, model red-teaming, and agent defense that prove value against FS success criteria like fraud reduction and compliance.
  4. Navigate Risk & Compliance: Serve as a domain expert on AI/model risk, operational resilience, and regulatory frameworks, leading technical responses for RFIs/RFPs and security questionnaires.
  5. Influence the Product Roadmap: Work cross-functionally with Engineering and Product teams to relay field feedback from FS customers, ensuring our AI security portfolio evolves with industry-specific needs.

Skills

Required

  • 5+ years in a customer-facing technical role (Solutions Engineer, Security Architect, or similar) within enterprise B2B SaaS.
  • Strong background in cybersecurity and AI, with hands-on understanding of LLMs, inference-layer guardrails, and data protection in production environments.
  • Practical familiarity with FS reference architectures, risk management, and compliance topics such as AML/KYC and data privacy.
  • Ability to translate complex AI security challenges into simple, actionable narratives for both technical teams and non-technical executives.

Nice to have

  • Experience supporting global banks or payment networks
  • Background in software/ML engineering before moving into customer-facing roles

What the JD emphasized

  • AI Runtime Security
  • securing AI inference
  • agentic systems
  • enterprise LLM deployments
  • AI security portfolio
  • AI/model risk
  • regulatory frameworks

Other signals

  • AI Runtime Security
  • securing AI inference
  • agentic systems
  • enterprise LLM deployments
  • AI security portfolio