Solutions Engineer — AI & Data Science Specialist

At F5, we strive to bring a better digital world to life. Our teams empower organizations across the globe to create, secure, and run applications that enhance how we experience our evolving digital world. We are passionate about cybersecurity, from protecting consumers from fraud to enabling companies to focus on innovation. Everything we do centers around people. That means we obsess over how to make the lives of our customers, and their customers, better.

And it means we prioritize a diverse F5 community where each individual can thrive.
** Role Overview
** F5 is expanding its
** AI Center of Excellence
** and is hiring a
** Specialist Solutions Engineer
** with deep expertise in
** AI, Data Science, and LLM behavior
** to support our
** AI Runtime Security
** portfolio.

This is a highly specialized SE role designed to fill a critical gap between
** customer-facing solution engineering
** and
** internal data science**. The primary focus of this role is to
** interpret, analyze, and explain AI security testing results**—particularly outcomes from Proof of Concepts (POCs), red-teaming exercises, and runtime guardrail evaluations.

You will act as the
** AI/ML subject-matter expert within the Solutions Engineering organization**, helping customers and internal teams understand:
* Why scanners trigger (or don’t)
* The tradeoffs between false positives and false negatives
* Model behavior under adversarial or ambiguous inputs
* How tuning, thresholds, and policy design impact real-world outcomes

Think of this role as a hybrid between a
** Solutions Engineer, Prompt Engineer, and Applied AI Analyst**, deeply technical, customer-facing, and outcome-oriented.
** What You’ll Do**### ###
** AI & Data Science Specialization
*** 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.### ###
** Customer & GTM Enablement
*** 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.### ###
** Internal Collaboration & Enablement
*** 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.
** What You Bring**###
** Required
* ** 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.### ###
** Strongly Preferred
*** Hands-on experience with prompt engineering, LLM evaluation, or model testing.
* Familiarity with AI security concepts such as:  + Prompt injection  + Jailbreaks  + Data leakage  +…