SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
F5 is seeking a Senior AI Software Development Engineer to lead the design, implementation, and optimization of enterprise-scale agentic AI systems. This is a highly technical, hands-on role focused on building production-grade AI agents using Google's Gemini and Vertex AI platforms.
Key responsibilities include architecting and optimizing enterprise-grade agent orchestration frameworks that support tool use, memory management, RAG (retrieval-augmented generation), and multi-agent collaboration patterns. You will develop secure integration patterns for agents interacting with enterprise systems like Salesforce, Snowflake, ServiceNow, and SharePoint, while building reusable SDKs and abstractions to standardize AI usage across F5 teams.
The role requires deep expertise in backend and distributed systems architecture, with hands-on proficiency in Python and at least one of Go, Java, or TypeScript. You must have proven production experience with LLM-based systems, including prompt engineering, tool calling, RAG implementations, and agent frameworks. Strong familiarity with Vertex AI, Gemini APIs, or similar enterprise AI platforms is essential.
You will also own observability, safety, and governance aspects—building logging and evaluation pipelines, implementing safety guardrails (input/output validation, hallucination mitigation, prompt injection defenses), and ensuring compliance with enterprise security standards. Additional responsibilities include enabling other engineering teams to adopt Gemini and internal AI development platforms through documentation, code samples, and technical guidance.
The ideal candidate brings 6+ years of software engineering experience, deep understanding of microservices and cloud-native architectures (Docker, Kubernetes), familiarity with vector databases and embedding pipelines, and strong knowledge of authentication and authorization patterns. Experience building multi-agent systems, model evaluation pipelines, and working with enterprise data platforms is preferred.
Success in this role means delivering a secure, scalable orchestration layer for enterprise agents, enabling teams to build production-ready AI applications with clean, reusable components, and accelerating AI adoption across engineering, sales, support, finance, and product teams.
