Artificial Intelligence Engineer

Software Engineer, AI Platform

Location:

New York City, five days onsite

Compensation:

$200,000 to $240,000 base, flexible for exceptional candidates

Equity:

0\.10% to 0\.25%

Employment:

Full-time

Visa Support:

H-1B transfers and TN applications supported

About the Company

We are partnering with a well-funded enterprise AI company building a coding agent that enables non-engineers to create production-grade applications using private company data.

The platform combines AI-powered application development with the security, governance, integrations, access controls, and observability required by global enterprises. Unlike consumer-focused AI builders, the company is focused on applications that support mission-critical business operations.

The company has raised $60 million from leading venture capital firms and prominent technology founders. Its small engineering team includes accomplished builders from some of the world’s most respected infrastructure and distributed-systems organizations.

Why Join

• Help build a frontier coding agent for enterprise application development
• Work directly with the CTO, a former founding engineer and architect at a leading distributed-systems company
• Join a small, highly technical engineering team with deep experience across Kafka, Kubernetes, distributed databases, enterprise security, and developer infrastructure
• Own critical systems immediately rather than operating within a narrow function
• Solve challenging problems across agentic AI, secure code execution, distributed systems, and enterprise governance
• Receive meaningful early-stage equity with significant potential upside
• Influence the architecture and technical direction of a rapidly growing AI platform
• Move through a fast interview process, with offers typically made within one to two weeks

What You Will Build

• AI coding agents that generate, execute, test, debug, and improve production software
• Continuous-learning systems using short-term memory, persistent memory, and organizational knowledge graphs
• Agent orchestration and feedback loops that improve accuracy, reliability, and task completion
• Secure execution environments for running AI-generated code
• Human and AI interaction patterns that help enterprise users build applications safely
• Centralized governance systems for applications, workflows, agents, secrets, permissions, and policies
• Backend and distributed systems capable of supporting large enterprise customers

What We Are Looking For

• Strong backend, platform, or distributed-systems engineering experience
• Experience building and shipping an agentic AI system or substantial LLM application in production
• Strong Python programming skills
• Experience designing backend systems, databases, APIs, and production architectures
• Understanding of LLM orchestration, tool use, evaluation, reliability, latency, and cost tradeoffs
• Experience with sandboxing, code isolation, containers, application security, or multi-tenant systems
• Evidence of exceptional technical ability through academic background, company experience, open-source work, or independently built products
• High agency and the ability to drive ambiguous projects from concept through production
• Willingness to work in the New York City office five days per week
• Interest in a demanding, fast-moving, and highly collaborative startup environment

Particularly Valuable Experience

• Coding agents or autonomous software-development tools
• Sandboxed or ephemeral code-execution environments
• Kubernetes, container runtimes, or infrastructure isolation
• Knowledge graphs, agent memory, or retrieval systems
• Model evaluation and production AI observability
• High-growth startups or respected infrastructure companies
• Master’s or PhD in computer science, artificial intelligence, machine learning, or distributed systems

The Environment

This is a high-ownership role for someone who wants to build at an unusually ambitious pace. Engineers are expected to own the complete product experience, learn emerging AI methods quickly, and contribute across traditional functional boundaries.

The company maintains a high hiring bar and is looking for exceptional builders rather than filling seats.