AI Software Engineering (Hybrid)

Cisco Systems•San Francisco, CA

1d•Hybrid

About The Position

The application window is expected to close on 12/30/2025. Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received. This is a hybrid role working 3 days a week in the San Francisco office. Meet the Team Foundation AI’s mission is to secure AI transformation. The Foundation AI team joined Cisco through the Robust Intelligence acquisition in fall 2024 to lead research and development of security and AI at Cisco. The team has deep expertise in AI and security and is an active contributor to cutting edge research and standards on AI and security. At Cisco, our mission is to build AI Security at Cisco scale as well as lead the next generation of AI infrastructure for disruptive security products across Cisco. About Robust Intelligence Robust Intelligence pioneered the category of AI Security and built the first platform for securing AI applications from supply chain, model vulnerabilities, and real time attacks. Funded by Sequoia and Tiger Global, Robust Intelligence customers include the world’s largest banking and financial institutions, HR and payroll services, FinTech and financial software, technology and consumer electronics, insurance, consulting, travel, data centers and cloud infrastructure, cybersecurity as well as government agencies. The company was acquired by Cisco in 2024. Your Impact Join Cisco's Foundation AI team and be at the forefront of AI and Security innovation. Here, you will solve ever-evolving challenges and leverage the dynamic AI landscape to craft solutions that transform the cybersecurity industry! As an AI Researcher on this team, you will create novel threat intelligence from open source and open weight AI supply chain sources. Our team has been featured publicly , and is making every security product at Cisco AI aware. As part of this team, you will have the chance to create and use ground breaking models and algorithms around AI for security. You'll gain deep expertise in the fields of both AI and security, engaging with all facets of generative AI techniques and their deployment in production environments. You will collaborate with a talented team of researchers, engineers, and security experts, and play a pivotal role in developing groundbreaking AI solutions. Shape the future of AI for Security with us and make an enduring impact on AI adoption across the world!

Requirements

A PhD in computer science, or related fields or Master’s with 2 years of related industry experience, or Bachelor’s with 4 years of related industry experience
Software engineering experience in programming languages such as Python or Golang
Experience in ML concepts like bias and variance, supervised & unsupervised learning, Generative AI

Nice To Haves

Experience developing software for a security/identity/privacy product
Experience deploying workloads in a cloud environment: GCP, Azure, AWS
Experience with Kubernetes
Familiar with traditional ML frameworks like PyTorch, TensorFlow, FastAI etc.
Familiar with or interested in developing proof-of-concept exploits for new or theoretical attacks
Experience reading papers in AI/ML and/or security and translating to prototype systems
Comfortable with fast iterative style development in an environment that requires autonomous thinking, risk taking and bias for action
Ability to use the latest GenAI technologies and creative prompting
Excellent written and verbal communication skills, strong analytical and problem-solving skills

Responsibilities

Track and analyze emerging AI systems, focusing on applications and environments related to security and safety
Develop a platform for AI intelligence gathering, data collection, model fine tuning, evaluation and other AI related needs
Work on purpose-built security foundational models
Author blog posts, white papers, or research papers related to emerging threats in AI security
Collaborate with cross-functional teams of researchers and engineers to translate research ideas into product features.
You'll also have the opportunity to contribute to our overall machine learning culture as an early member of the team.

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