AI Engineer (New York)

Edra Inc.; New York (NY); On-site; USD 130,000 - 195,000; Full time

Job summary

Edra Inc. is building a learning system that teaches AI agents how enterprises actually work. We ingest knowledge bases, conversations, tickets, and logs to produce executable instructions with confidence scoring—deciding when to automate or escalate to humans.

We seek AI Engineers who have built production LLM-based systems, scaled workflows, and designed evaluation frameworks for enterprise deployments. Join a deeply technical team in New York and contribute to core learning libraries and

Qualifications

• Built complex, production-grade LLM-based systems.
• Experience scaling LLM workflows handling millions of requests.
• Experience with agent-based systems and enterprise deployments.

Responsibilities

• Build and extend core context-learning library.
• Design and implement LLM-powered systems and agentic workflows.
• Build agentic features for knowledge management.
• Build reliability and confidence systems with evaluation & confidence scoring.
• Architect asynchronous, scalable systems for AI orchestration.

Skills

LLM systems

Production scaling

Multi-agent systems

Evaluation frameworks

Self-directed

Job description

About Edra

Edra is solving one of the hardest problems in enterprise AI: AI models are generic but company processes are specific. We build AI agents that learn how processes actually run, and then run their operations.

We're a Series A startup, backed by Sequoia and other leading VC firms, led by Co-Founders who created and led Forward Deployed AI Engineering at Palantir, and we're growing our team in New York and London. We're a deeply technical team of engineers, AI researchers, and strategists with a high bar for talent and a shared belief that exceptional people are the foundation of everything great we'll build.

The Role

We're building a learning system that teaches AI agents how enterprises actually work. Our system ingests knowledge bases, conversations, tickets, and system logs, then produces written instructions that agents can execute–with confidence scoring to know when to automate and when to seek human input.

We're looking for AI Engineers who have built complex, production LLM-based systems. Whether you've scaled LLM workflows handling millions of requests, built multi-agent systems in production, or designed evaluation frameworks for enterprise deployments, we want people who bring intensity and self-direction to their craft.

You’ll spend most of your time advancing our core learning library and building the harness that powers our platform’s agents across all customers. The work spans continuous learning systems, agentic features, human-in-the-loop feedback loops, and agent orchestration.

What You'll Do

• Build and extend our core context-learning library, turning customer-informed problems into reusable platform capabilities.

• Design and implement LLM-powered systems and agentic workflows from concept to production

• Build agentic features for knowledge management–think agents that can edit, update, and maintain large knowledge bases autonomously

• Build reliability and confidence systems–evaluation frameworks, confidence scoring, and logic for when to automate vs. when to elevate to a human

• Architect async, scalable systems that handle complex AI orchestration