Founding Engineer – Applied AI

About GhostEye

GhostEye is defining Human-Centric Security Validation — a new category that validates whether people would resist social engineering attacks before attackers discover who won’t. We’re on a mission to fix what’s actually getting breached: not technical vulnerabilities, but humans who are never tested until it’s too late.

Our Progress

Fresh out of Y Combinator S25, we’re serving mid-market and enterprise customers across financial services, consumer, and technology.

What You’ll Do

• Own our multi-modal AI stack from OSINT agents to voice agents delivering realistic social engineering attacks
• Build MCP servers to enhance agent capabilities and architect agentic memory layers for optimal context delivery
• Develop agent evaluation frameworks and fine-tune SLMs to optimize social engineering campaign outputs
• Collaborate with RL researchers and offensive security experts to build autonomous red-team agent swarms
• Deploy production AI agents using vector databases, LLM observability stacks, and modern orchestration tools
• Research and publish on multi-agent systems best practices

Requirements

• Deep expertise in Python and Go for building scalable backend systems
• Strong experience with vector databases, context engineering, and agentic memory/orchestration
• Hands-on experience operating and leveraging LLM observability stacks
• Proficiency with containerization (Docker) and orchestration (Kubernetes, AWS)
• Experience with major cloud providers (AWS) and CI/CD best practices
• Commitment to writing high-quality, maintainable, and well-tested code

Your Impact

• Define the next generation of AI-native security validation at enterprise scale
• Protect hundreds of thousands of employees at Fortune 500 companies from social engineering attacks
• Work at the cutting edge of multi-agent systems and security research
• Own entire AI features from research to production with no bureaucracy
• Shape engineering culture and practices as we grow

Tech Stack

AWS, Kubernetes, Clickhouse, Kafka, Redis, Postgres, Langsmith, Python, Go

Interview Process

1. Phone Screen (30 min, remote) – Chat with a founder about your background and GhostEye
2. Technical Assessment (3-4 hours, take-home) – Build a small feature
3. On-Site Interview (NYC) – Present your work, meet the team, and join us for a meal
4. Offer

You’ll work directly with the founders throughout. Steps 1-2 are remote, steps 3-4 are in NYC. We move fast—expect feedback within 48 hours of each stage.

Compensation & Benefits 

• $100K – $225K + Equity (0.25% – 1.5%)
• Full Health Insurance Covered.
• Gym Stipend + Whoop/Oura Memberships