AI Systems Engineer: LLMs, Autonomous Agents, Scale

DeepRec.ai; New York (NY); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive base salary

Equity

Health, dental, and vision coverage

Flexible PTO

Home workspace setup

Office meals, snacks, and drinks

Location-appropriate benefits

Job summary

DeepRec.ai is building a learning system that helps AI agents understand how enterprises operate by ingesting knowledge bases, conversations, tickets, and system activity to create structured instructions for AI agents with built-in confidence and control.

The team designs and deploys LLM-powered workflows, builds autonomous agents for knowledge management, and develops reliability, evaluation, and product direction in a fast-paced, in-person environment.

Qualifications

• Experience building complex, production LLM-based systems, and the ability to speak to the engineering decisions and tradeoffs behind them
• A track record of shipping meaningful software or AI systems to production and iterating on them based on real-world usage
• Experience building agents, autonomous systems, or sophisticated LLM workflows
• Genuine interest in systems that improve continuously through human feedback, evaluation, prompt optimization, and context engineering
• Comfort operating at the boundary between AI research and production engineering
• Strong systems-design chops, particularly with asynchronous and distributed architectures
• Excellent written and verbal communication — able to explain technical concepts to both technical and non-technical stakeholders
• 3+ years of professional engineering experience

Responsibilities

• Building and extending a core context-learning platform, turning real customer problems into reusable AI capabilities
• Designing and implementing LLM-powered systems and agentic workflows from concept through production
• Building autonomous agents for knowledge management — systems that can create, edit, update, and maintain large knowledge bases
• Developing reliability and confidence mechanisms, including evaluation frameworks and decision logic for automate-vs-escalate calls
• Architecting asynchronous, scalable infrastructure to support complex AI orchestration
• Building systems that learn and improve through human feedback, evaluation, and iterative optimization
• Contributing to the company's AI strategy, technical architecture, and product direction

Job description

DeepRec.ai is building a learning system that helps AI agents understand how enterprises operate by ingesting knowledge bases, conversations, tickets, and system activity to create structured instructions for AI agents with built-in confidence and control.

The team designs and deploys LLM-powered workflows, builds autonomous agents for knowledge management, and develops reliability, evaluation, and product direction in a fast-paced, in-person environment.