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 |
|---|---|---|
| Senior Site Reliability Engineer, AI Inference The AI Inference Engineer optimizes Large Language Models (LLMs) for inference across diverse environments, focusing on maximizing throughput, minimizing latency, and maintaining model accuracy. This role involves building and maintaining inference engines, optimizing models for specialized hardware, designing auto-scaling architectures, and establishing robust observability frameworks for enterprise-grade reliability. | Serve | 8 |
| AI Inference Engineer AI Inference Engineer responsible for optimizing Large Language Models (LLMs) for inference across various environments, focusing on maximizing throughput, minimizing latency, and maintaining accuracy. This role involves building and maintaining inference engines, optimizing for hardware acceleration, designing auto-scaling architectures, and establishing performance monitoring frameworks. | Serve |
| 8 |
| Global Solutions Architect - Security and AI This role is a technical leadership position supporting Sales in the area of AI specialization. The Global Solutions Architect (GSA) collaborates with Sales teams to identify F5 solutions for customer needs, provides technical expertise, and acts as an evangelist and thought leader in AI. They also provide feedback to product management and services teams and mentor the Solution Engineering community. The role requires advanced knowledge of AI practices, cloud-native application design, and the delivery/security of LLM models for AI inference. | Serve | 5 |
| Sr Software Development Engineer This role focuses on Release Engineering, automating and managing product releases across software and SaaS platforms. A key aspect is integrating AI-driven workflows and tools into CI/CD and release management pipelines to enhance efficiency and quality, particularly within public cloud marketplace contexts. | Serve | 5 |
| Site Reliability Engineer III Site Reliability Engineer III for the Unified Demo Framework (UDF) platform team, focusing on launching and managing F5 Guardrails and Redteam product lines. The role involves designing, deploying, and supporting Kubernetes environments for AI workloads, optimizing system performance, and ensuring reliability. Responsibilities include Kubernetes orchestration, observability, automation, and collaboration with product teams. | Serve | 5 |
| Cloud Support Engineer (SRE Development) This role is for a Cloud Support Engineer with a focus on Site Reliability Engineering (SRE) within a SaaS environment. The candidate will be responsible for running, supporting, and scaling an AI Security Public SaaS platform, including operating AI inference workloads at scale. Key responsibilities include proactive monitoring, customer-centric incident response, collaboration with development teams, and contributing to building scalable infrastructure for AI inference. | Serve | 5 |