---
title: 'AI Engineer, Agent Infrastructure at Zed'
canonical: 'https://feeny.ai/job/ai-engineer-agent-infrastructure-zed-san-francisco-7vmbp3jws5x3'
type: 'job'
last_seen: '2026-09-07'
---

# AI Engineer, Agent Infrastructure at Zed

- **Company:** Zed
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-05-22
- **Last confirmed live:** 2026-09-07
- **Apply:** https://jobs.ashbyhq.com/zedfinancial/f6f294eb-5659-46d0-a9c6-480e6eb4852b

## Job description

## 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.

## About Zed

## Company Overview
- **One-liner**: Zed builds a modern, AI-powered credit card and financial platform designed for young professionals in Southeast Asia, offering no-interest credit, unlimited virtual cards, and transparent fees.
- **Entity Type**: Private (Series A; total funding $22.5M)
- **Headquarters**: San Francisco, California, United States (with operations in Manila, Philippines)
- **Founded**: Year not publicly stated; launched in Philippines in 2024
- **Founders**: Steve Abraham (Co-founder) & Danielle Cojuangco Abraham (Co-founder & Co-CEO)

## Core Business
- **Primary industry**: Financial Services (Consumer Fintech)
- **Target customers**: B2C; specifically young, college-educated professionals in Southeast Asia (Generation Z and Millennials) who are underserved by traditional credit systems.
- **Mission statement**: "To build a bank for the next generation that feels like a great private banker," unlocking wealth creation for young people by democratizing access to responsible credit.

## Products & Services
- **[Zed Credit Card]**: A premium Titanium Mastercard with no interest, no foreign transaction fees, and unlimited virtual cards. Features include a data-driven application process that uses AI to underwrite creditworthiness from non-traditional data (transaction data, financial documents), flexible installment plans, instant card locking, and single-use virtual cards for online security. Type: Fintech product (credit card + mobile app).

## Market Standing
- **Valuation**: Not disclosed
- **Key Metric**: Total funding of **$22.5M** (Seed: $6M led by Valar Ventures; Series A: $16.5M led by Accel). Waitlist has nearly **200,000 sign-ups**; customer base has **grown by 10x** and monthly Gross Merchandise Value (spend) has grown by **~500%** since the beginning of 2025.
- **Notable Investors/Partners**: Accel, Valar Ventures, Immad Akhund (CEO of Mercury), Dalton Caldwell (former Y Combinator). Issued in partnership with Mastercard. Regulated by the Philippine Central Bank (BSP).
- **Growth Signals**: Rapid growth in user base and transaction volume; Series A round led by top-tier VC Accel; strong word-of-mouth waitlist; expansion of an AI-driven underwriting model targeting a massive underserved market (200M+ college-educated young professionals in emerging Asia). The team has grown **+35% YoY** (13 employees).

## Competitive Advantages
- **AI-native underwriting**: Uses foundational models to assess creditworthiness from alternative data (transaction history, financial documents) rather than relying on thin or nonexistent traditional credit bureau files. This unlocks credit for a huge "unscoreable" demographic.
- **Bespoke product for a generation**: The card is designed specifically for the spending habits of young Southeast Asians (travel, online shopping, peer-to-peer payments) with features like no foreign transaction fees and unlimited virtual cards.
- **Founder-market fit & licensing**: Founded by Stanford-educated engineers with deep fintech expertise (Symple, Y Combinator, Box) and local market knowledge. The company holds a financial institution license from the BSP, a significant regulatory moat.
- **Purpose-built tech stack**: Building a modern bank from scratch, free from legacy infrastructure, allowing for AI-driven, safety-critical consumer systems and multi-currency payments.

## Strategic Focus
- **Expand AI-driven credit products**: The current underwriting model is just the first application; the company plans to leverage proprietary AI models to build a wider suite of banking services for its target demographic.
- **Scale in Southeast Asia**: Currently focused on the Philippines as a beachhead market, with a long-term goal of serving young consumers across the region and globally.
- **Hire for product & engineering**: Actively recruiting product-minded engineers, designers, data scientists, and operations staff to build the core platform.
- **Key priorities**: Real-time credit decisioning with sparse data, building safety-critical consumer systems, multi-currency payments, and AI-driven customer experiences.

## Why Work Here
- **High-impact mission**: Opportunity to build a fundamental piece of financial infrastructure for a generation of 200M+ underserved young professionals in Asia.
- **Talent & culture**: The team is described as "ambitious" and "radically honest," composed of Stanford engineers and veterans from Square, Google, Stripe, Facebook, and Box. The environment is "people-first" and focused on technical excellence.
- **Work model**: Hybrid/Office for different teams. Product, Design, and Engineering teams are headquartered in **San Francisco**, while Operations and Risk are based in **Manila**.
- **Backing and stability**: Backed by top-tier investors (Accel, Valar) and key fintech leaders, providing strong financial runway and strategic guidance.
- **Cutting-edge work**: Engineers work on hard problems like AI underwriting, real-time credit, and multi-currency payments with the latest tools (foundational models, agent infrastructure).

## Sources
1. [zed.co](https://www.zed.co/)
2. [LinkedIn - Zed](https://www.linkedin.com/company/zedfinancial)
3. [Zed - Series A Announcement](https://www.zed.co/announcement-series-a/)
4. [Zed - Company Page](https://www.zed.co/company/)
5. [Zed - Careers Page](https://jobs.ashbyhq.com/zedfinancial)
6. [Zed - Card Page](https://www.zed.co/)

## Other roles at Zed

- [Lead Product Designer](https://feeny.ai/job/lead-product-designer-zed-san-francisco-bc3vavgakga1) — San Francisco, CA
- [Partnerships Lead](https://feeny.ai/job/partnerships-lead-zed-manila-zwf9wkssaxth) — Manila, Philippines
- [Senior ML Data Scientist (Credit Risk)](https://feeny.ai/job/senior-ml-data-scientist-credit-risk-zed-san-francisco-5ajvgnd0y8s6) — San Francisco, CA
- [Customer Experience & Operations Analyst](https://feeny.ai/job/customer-experience-operations-analyst-zed-manila-rdykm2kys848) — Manila, Philippines
- [Product Engineer](https://feeny.ai/job/product-engineer-zed-san-francisco-68gj119nab78) — San Francisco, CA
- [Data Scientist](https://feeny.ai/job/data-scientist-zed-manila-y8xamvdpgzgn) — Manila, Philippines