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This role is within our AI Governance team, a critical area addressing the growing need for secure and managed AI adoption in enterprises. As AI becomes integral to business processes, companies require robust solutions to track usage, protect data, and control access. The AI Governance team is at the forefront of building these essential solutions.

As a Software Engineer II on the AI Governance team, you will play a pivotal role in shaping a new product category focused on AI usage control. You will contribute to building systems that ensure AI applications are attributable, policy-compliant, budget-aware, and auditable in real-time.

Key responsibilities include developing high-quality, reliable AI governance products with exceptional attention to detail. You will drive rapid, iterative product improvements, actively incorporating customer feedback to continuously enhance the product. This involves designing and implementing critical components such as MCP access controls, model gateway policies, runtime authorization mechanisms, audit pipelines, and usage attribution systems.

This is a high-impact position offering the opportunity to tackle ambiguous challenges from inception to production. You will leverage AI-native development practices to boost engineering velocity while upholding rigorous standards for correctness, security, and overall quality. Close collaboration with Product, Security, Legal, IT, and other engineering teams will be essential for making informed trade-offs and delivering significant customer value.

We are seeking a Software Engineer II with a minimum of 3 years of experience in building and operating production systems. While proficiency in Python, Go, Django, React, MongoDB, or AWS is advantageous, it is not a strict requirement.

Ideal candidates possess strong software engineering fundamentals, with a proven track record of developing reliable, maintainable, and well-architected systems. A high degree of initiative and a bias towards shipping are essential, enabling you to transform ambiguous problems into manageable, incremental releases and establish fast feedback loops.

An AI-native engineering mindset is crucial, including practical experience using AI tools to enhance development velocity without compromising correctness, security, or quality. We value curiosity and a commitment to continuous learning, with the ability to rapidly grasp new technologies, unfamiliar domains, and evolving customer needs. Strong product ownership, a focus on solving real customer problems, and delivering measurable impact are key.

Sound judgment in security and systems, particularly concerning identity, authorization, data movement, policy enforcement, or auditability, is highly desirable. Excellent written and verbal communication skills are necessary for effective collaboration across diverse engineering and non-engineering teams. Familiarity with AI infrastructure, model gateways, MCP, developer tools, identity systems, or data protection is a plus.