Role Summary We’re building a new category of enterprise security infrastructure for modern, AI-driven systems. As a backend engineer, you’ll work on the core systems that power policy management, threat evaluation, observability, and integrations with external systems—enabling enterprises to evaluate threats, enforce policies, and gain visibility into agentic and API-driven workloads. You’ll also play a key role in shaping how AI and agentic systems are built, orchestrated, and secured in production, working on real-world applications of LLMs and autonomous workflows. This is a hands-on role for someone who enjoys building from first principles and shipping systems that operate reliably at scale. What you’ll do Design and build systems for policy definition, enforcement, and real-time decision workflows, incorporating AI and agentic technologies Build and evolve systems that support agent orchestration, reasoning workflows, and secure execution patterns Develop a robust integration layer connecting with cloud platforms, APIs, and third-party systems Build infrastructure for telemetry, logging, and auditability, including visibility into agent behavior and decisions Design extensible APIs and data models across relational, NoSQL, and graph-based systems to power intelligent systems Own problems end-to-end—from shaping requirements to production rollout and iteration Work closely with product and engineering to define what should be built, not just how What we’re looking for 4+ years of experience building backend or distributed systems Strong in one or more: Python, Go, Java, or TypeScript Experience building and operating systems in production environments Experience working with APIs and integrations (REST, event-driven, or streaming systems) Comfortable navigating ambiguity and making forward progress without perfect information Bonus: Former experience as early engineer at a startup Experience in security, infrastructure, or networking Experience integrating with cloud providers or external SaaS systems Familiarity with observability systems, knowledge graphs, or complex data modeling Hands-on experience or strong interest in LLMs, agentic systems, or AI-powered workflows What makes someone successful here You take ownership of problems and drive them to completion You think in systems and workflows, including how they interact with external environments You care deeply about reliability, debuggability, and performance You design for extensibility and integration from day one You’re curious about how AI systems behave in production and how to make them safe and reliable You’re energized by building in areas without established playbooks Why this role You’ll help define how enterprises secure agentic and autonomous systems You’ll solve problems at the intersection of systems, security, and AI You’ll have real ownership and influence over the direction of the product You’ll build systems from the ground up in a fast-moving environment Compensation The base pay range for this role is $150,000 – $200,000 per year.
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