AI Engineer, Agent Infrastructure
Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on May 22, 2026.
About Zed
Zed is building the first AI-native, licensed neobank in the Philippines designed to democratize access to premium financial services for young professionals in global markets. The current banking system is broken, often shutting out the world’s youngest and fastest-growing consumer classes-we’re here to fix it.
Our team is uniquely positioned to solve this. We are Stanford engineers and former YC founders who have spent our careers at the intersection of banking and hyper-growth startups like Square, Facebook, and Box. We’ve been here before, having previously built and exited Symple (YC W'17), a fast-growing B2B payments company.
We are backed by world-class investors, including Accel, Valar, Immad Akhund (Mercury), Dalton Caldwell (Y Combinator), and Kunal Shah (Cred).
The Role
We're hiring an engineer to own the infrastructure layer behind our production AI agents.
This is not a prompt engineering role. It's not a UI role. It's about the harness around LLMs - the systems that determine how agents actually execute tasks, interact with tools, access internal and external systems, stay within permission boundaries, and behave reliably in production.
You'll sit at the intersection of backend infrastructure and product, and what you build will define how AI is deployed across the company.
What You’ll Work On
Build and own the execution layer for AI agents - task orchestration, tool calling, state management
Define how agents interact with internal systems and external APIs
Design sandboxed environments and permissioning models for safe, controlled agent execution
Build evaluation, monitoring, and debugging infrastructure for agent behavior in production
Integrate agents into real product workflows where correctness and reliability are non-negotiable
Improve system performance across latency, cost, and quality tradeoffs
What You Bring
Direct experience shipping production LLM or agent systems end-to-end - orchestration, evaluation, reliability, not just prototypes
Strong backend or infrastructure engineering foundation (distributed systems, APIs, platform engineering)
Experience with workflow orchestration, automation systems, or agent frameworks
Familiarity with evaluation and observability loops for AI systems
Ability to think across both infrastructure concerns and product behavior - this role requires both
Strong Signals
You've built agent systems that take real actions, not just generate text
You've designed execution environments - task runners, sandboxes, job systems
You've worked on AI that's deeply embedded in a real product, not a side project or internal tool
You have experience with observability and evaluation loops for AI systems in production
Why This Role
Most teams are still prototyping. We're past that.
This role determines whether our agents are reliable or brittle, safe or risky, useful or demo-only. You'll be building the layer that makes production AI actually work - at a company where AI is core to how we underwrite, operate, and scale.
We hire exceptional people from diverse backgrounds because different perspectives build better products.
If you’re excited about this role but don’t check every box, apply anyway. We value potential, ownership, and alignment with our values more than perfect résumés.
We are an equal opportunity employer and do not discriminate based on legally protected characteristics. We provide reasonable accommodations throughout the hiring process.
Compensation includes salary, equity, and benefits. Final offers are based on role scope, location, and experience.