Solutions Engineer — AI & Data Science Specialist

F5 is a company dedicated to enhancing the digital world, focusing on cybersecurity and application management. They are looking for a Solutions Engineer — AI & Data Science Specialist to support their AI Runtime Security portfolio, requiring deep expertise in AI and Data Science to interpret and explain security testing results to customers and internal teams.

Responsibilities:

• Analyze and interpret results from AI Runtime Security POCs, including red-team campaigns, prompt/response scans, and inference-layer inspections
• Diagnose false positives and false negatives, explaining root causes in clear, customer-friendly language
• Help define acceptable risk thresholds and success criteria for enterprise AI security deployments
• Partner with customers to refine prompts, policies, scanner descriptions, and evaluation strategies
• Act as the escalation point for complex AI behavior questions during evaluations and pilots
• Partner with Account Executives and core Solutions Engineers during late-stage evaluations and technical deep dives
• Support customer workshops focused on AI testing methodology, evaluation frameworks, and AI risk interpretation
• Translate model behavior and statistical outcomes into business-relevant narratives (risk, compliance, trust, readiness)
• Assist in shaping POC readouts, executive summaries, and customer-facing reports
• Serve as the bridge between Solutions Engineering, Product, and Data Science when interpreting scanner performance and model behavior
• Help define internal best practices for: FP/FN analysis, evaluation datasets, prompt and policy tuning, scanner validation strategies
• Create internal guidance, playbooks, and examples to raise the overall AI literacy of the SE team
• Provide feedback to Product and Engineering based on real-world customer testing patterns

Requirements:

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, AI, or a related technical field
• 5+ years of experience in a technical, customer-facing role (Solutions Engineer, ML Engineer, Data Scientist, Applied AI Engineer, or similar)
• Strong understanding of: Large Language Models (LLMs), Prompt engineering and prompt evaluation, Model behavior, bias, and limitations, False positive / false negative tradeoffs in ML systems
• Experience analyzing model outputs, classification results, or evaluation metrics
• Ability to explain complex AI/ML concepts clearly to non-data-scientists
• Hands-on experience with prompt engineering, LLM evaluation, or model testing
• Familiarity with AI security concepts such as: Prompt injection, Jailbreaks, Data leakage, Model misuse and abuse patterns
• Experience working with real customer datasets or evaluation pipelines
• Comfort working with Python, notebooks, or lightweight analysis tooling (even if not production-focused)