Solutions Engineer - AI Security - Fin Services

F5 F5 · Enterprise · Singapore

Solutions Engineer focused on AI Security for Financial Services customers, working with F5's AI Runtime Security portfolio to secure AI inference, agentic systems, and LLM deployments. Responsibilities include driving the sales motion, designing tailored architectures, executing demos, navigating risk & compliance, influencing product roadmap, and ensuring customer success.

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
  • Hands-on understanding of LLMs
  • Hands-on understanding of inference-layer guardrails
  • Hands-on understanding of data protection in production environments
  • Practical familiarity with FS reference architectures
  • Practical familiarity with risk management
  • Practical familiarity with 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
  • Generative AI
  • AI security
  • AI/model risk
  • regulatory frameworks
  • FS success criteria
  • FS customers
  • FS environments
  • FS reference architectures
  • FS security reviews

Other signals

  • AI Runtime Security
  • Generative AI
  • securing AI inference
  • agentic systems
  • enterprise LLM deployments
  • model risk
  • operational resilience
  • regulatory frameworks