Job Description

Location: San Francisco, CA (Onsite | Remote)

About VirtueAI

Virtue AI is at the forefront of AI security. As enterprises increasingly adopt Large Language Models, the need for robust, trustworthy, and safe AI has never been greater. Our mission is to build the essential guardrails and red-teaming tools that enable organizations to deploy multi-modal AI applications confidently and responsibly.

We are a well-funded, early-stage startup founded by industry veterans, and we're looking for passionate builders to join our core team.

Are you a high-performing, motivated engineer ready to make a significant impact in the AI security space? Virtue AI is seeking talented AI Platform Engineer to join us. We are a fast-paced, customer-focused company with cutting-edge technology, strong early customer traction, and market dominance. If you thrive in an environment that values hard work, collaboration, and technical curiosity, we want to hear from you.

The Role

As a Software Engineer at Virtue AI, you will design and implement the distributed systems and APIs that power our AI security products. From high-throughput inference services to multi-tenant data pipelines and secure packaging for customer-managed deployments, your work will form the backbone of our platform.

You will collaborate closely with ML engineers, security experts, and product leads to build reliable, scalable, and secure systems that run across SaaS and on-prem environments. This is a high-impact role where clean abstractions, thoughtful APIs, and rock-solid systems engineering multiply the productivity of the entire team.

Key Responsibilities

• Design, implement, and maintain scalable services and APIs for red-teaming, guardrails, and agent-safety products.
• Build robust, multi-tenant data pipelines and storage layers that support real-time evaluation and analytics at enterprise scale.
• Develop abstractions for deployment across heterogeneous environments (SaaS, customer Kubernetes clusters, hybrid cloud).
• Partner with ML engineers to integrate inference services (vLLM, Triton, Ray) into secure, production-grade systems.
• Implement observability and performance tooling (latency, throughput, reliability) to meet enterprise SLOs.
• Contribute to CI/CD pipelines, containerization workflows (Docker, Helm), and deployment automation.
• Participate in design reviews, code reviews, and documentation to ensure long-term maintainability.

Qualifications

• Strong programming experience in Python, Go, or a similar language.
• Solid understanding of distributed systems, concurrency, and service-oriented architecture.
• Experience with SQL and NoSQL databases (e.g., Postgres, Redis, MongoDB).
• Hands-on experience with containerization and orchestration (Docker, Kubernetes).
• Familiarity with cloud services (GCP, AWS, or Azure) and infrastructure as code (Terraform).
• Comfort working in fast-paced environments with a focus on secure, reliable delivery.

Bonus:

• Background in building SaaS or enterprise software with on-prem deployment requirements.
• Experience integrating with ML inference frameworks or GPU-accelerated backends.

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