Job description

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

Requirements

Must-haves

We’re building a new category of enterprise security infrastructure for modern, AI-driven systems.
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

Nice-to-haves

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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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Platform: gem
Effort: medium