F5 currently has 33 active AI-related job listings. The majority of these roles, 52%, are focused on agents. Engineering is the top hiring function. Over the last 30 days, F5 posted 9 new AI roles, representing a 53% decrease compared to the previous 30-day period.
Currently tracking 20 active AI roles, down 11% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $124k–$235k (avg $175k).
F5 currently has 32 active AI-related roles in our index. The most common open titles are: Software Development Engineer - II (2), Sr. Software Engineer - Agentic AI (2), AI Deployment Engineer, AI Inference Engineer, Business & AI Data Analyst III. Most positions are in Engineering and Product.
F5's active AI hiring is concentrated in: agents (47%), application (22%), serving infrastructure (19%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
F5 is hiring AI talent in: United States (10 roles), India (6 roles), Ireland (4 roles), United Kingdom (2 roles).
Job postings at F5 most frequently reference: llm observability, guardrails, agent orchestration, model serving, inference infra.
In the past 30 days, F5 has posted 12 new AI-related roles. That is a +33% change versus the prior 30 days (9 → 12).
| Title | Stage | AI score |
|---|---|---|
| AI Data Engineer AI Data Engineer responsible for building and optimizing data pipelines for AI model training and automation initiatives within corporate operations. Focuses on data quality, integrity, and availability for AI systems, with a strong emphasis on Python, SQL, and big data frameworks. | Data | 7 |
| Principal Product Manager - AI Data Quality Product Manager to architect and scale an AI-Ready Data Quality Platform built on Databricks and Unity Catalog. The role focuses on defining and shipping platform capabilities for an AI Data Fabric, including real-time anomaly detection, schema enforcement, and automated data contract validation. It emphasizes treating data quality like SRE treats uptime and driving data ownership as a product discipline, aligning catalog metadata with AI feature stores and inference pipelines. | DataEval Gate |
| 7 |