Principal AI Engineer

@ F5

About F5

At F5, we strive to bring a better digital world to life. Our teams empower organizations globally to create, secure, and run applications that enhance the digital experience. We prioritize cybersecurity, innovation, and a diverse community where every individual can thrive.

Why this role matters

This role is critical as F5 scales its SaaS and subscription offerings. The Principal AI Engineer designs, builds, and operates AI systems that drive self-service, agent assist, and knowledge automation, improving customer satisfaction, deflection, MTTR, and agent productivity.

Position Summary

The Principal AI Engineer leads technical vision for AI systems within Customer Success & Support. You will transform product needs into robust ML architectures, manage model lifecycles with MLOps best practices, implement safe RAG/LLM systems, and collaborate with cross-functional teams to deploy production-grade solutions.

Key Responsibilities

• Define architecture and roadmap for AI capabilities in support workflows.
• Lead the end-to-end model lifecycle: data pipelines, training, evaluation, and deployment.
• Develop production-quality ML services and APIs using Python.
• Implement safety, privacy, and governance controls for generative systems.
• Integrate AI components with Salesforce, myF5 portal, Azure/AWS, and other platforms.
• Monitor KPIs such as CSAT, deflection rate, SLA compliance, and model accuracy.
• Prototype and iterate on new models, ensuring practical production use.
• Mentor engineers and data scientists, setting best practices for model experimentation and CI/CD.

What Success Looks Like

Achievement of measurable improvements in self-service adoption, case deflection, agent productivity, and overall efficiency in support operations.

Required Qualifications

• 10+ years of software engineering experience with focus on ML/AI systems.
• Strong programming skills in Python and production-level service development.
• Deep expertise in machine learning: training, evaluation, and productionization.
• Hands-on experience with LLMs, including fine-tuning and prompt engineering.
• Solid background in MLOps, data engineering, and large-scale data processing tools.
• Experience with cloud platforms (AWS/Azure) and integration with enterprise systems.

Preferred Qualifications

• Experience in AI for customer support and knowledge management.
• Expertise in regulated environments with compliance controls.
• Exposure to multi-modal models and vector databases.
• Proven record mentoring engineering teams.

Skills & Behaviors We Value

We value a strategic and collaborative mindset, data-driven decision making, and pragmatic approaches to AI innovation while focusing on customer outcomes and operational efficiency.

Key skills/competency

• Python
• ML/AI
• MLOps
• LLM
• NLP
• Data Pipelines
• Cloud
• APIs
• Automation
• Compliance