Senior Software Engineer – Agentic AI Tools

F5•San Jose, CA

7d•$166,100 - $249,100•Hybrid

About The Position

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. We are seeking an innovative and highly skilled Software Engineer III specializing in agentic AI tool building to lead the development and deployment of AI agents, tools, and models. This role primarily focuses on creating autonomous AI agents that support threat research by integrating external sources such as CVE databases, vulnerability feeds, threat intelligence APIs, scraped articles, and trending topics, along with internal sources such as F5 product deployment data and telemetry. These agents will accelerate research across AI security, application security, bots, post-quantum cryptography, and other emerging cybersecurity areas. In addition, this role will build AI-driven technical marketing tools and broader AI-powered security tools that translate security and non-security insights into demos, dashboards, technical content, and customer-facing assets. You will work closely with product management, architects, technical marketing engineering, software engineering, and threat research experts to create AI-driven tools that support both deep technical research and practical security storytelling.

Requirements

8+ years of experience in AI/ML engineering, including recent hands-on work building and deploying agentic AI systems for research, automation, and intelligence generation.
Strong expertise in Python and in designing and orchestrating autonomous and multi-step AI agents for research and security workflows.
Hands-on experience with LangChain, LangGraph, CrewAI, and LlamaIndex.
Working knowledge of OpenAI, Anthropic, Gemini, and NVIDIA model ecosystems.
Experience with RAG architectures, prompt engineering, tool calling, embeddings, vector databases, and workflow design for reliable AI agents.
Experience with MLflow, Kubeflow, BentoML, and related MLOps and AI deployment tools.
Strong expertise in data ingestion using APIs, web scraping, BeautifulSoup, and Scrapy, including pipelines for CVEs, vulnerability databases, threat feeds, blogs, and other external/internal data sources.
Foundational understanding of cybersecurity concepts and frameworks such as MITRE ATT&CK and OWASP.
Proven success delivering AI-driven research tools, security and non-security tools, scalable automation, and technical outputs that improve technical marketing engineering assets such as demos, articles, testing workflows, webinars, presentations, and reusable validation tools.
Strong cross-functional collaboration skills across engineering, product management, technical marketing engineering, research, and data science teams.

Nice To Haves

Familiarity with F5 products such as AI Security, BIG-IP, NGINX App Protect, and Distributed Cloud API Security, or equivalent platforms, is nice to have.

Responsibilities

Build and implement AI agents that autonomously scrape, ingest, correlate, and analyze data from external and internal sources to support threat research and broader security use cases.
Build agents using Python, TypeScript, and where relevant Go, along with LangChain, LangGraph, CrewAI, LlamaIndex, APIs, web scraping libraries, and ML frameworks for predictive analytics and research workflows.
Enhance F5 platform and portfolio integration, including AI Security, BIG-IP, NGINX, and Distributed Cloud, with AI agents and supporting tools for scalable research, security analysis, and technical marketing engineering assets.
Engineer AI-driven agents to detect, analyze, and assess emerging threats across AI security, app security, bots, PQC, and related trends.
Turn research findings into usable outputs for internal teams and customer-facing security narratives.
Partner with technical marketing engineering teams to improve the quality, scale, and effectiveness of demos, technical articles, webinars, presentations, automation, and use case validation.
Develop AI-powered security and non-security tools, dashboards, and web experiences for technical marketing, demos, presentations, testing, and research.
Build pipelines for AI workload optimization, observability, testing, and automation across research and technical marketing engineering use cases.
Support validation and testing of security tools, demo environments, and customer use cases to improve repeatability and technical depth.
Develop AI agents and tools independently or in close collaboration with product management, architects, technical marketing engineering, software engineering, and threat research teams.
Adapt tools and workflows to evolving business priorities, including broader security and non-security opportunities.