The Opportunity Our client is building a learning system that helps AI agents understand how enterprises actually operate. Their platform ingests information from sources like knowledge bases, conversations, support tickets, and system activity, then converts it into structured instructions that AI agents can execute - with built-in confidence and reliability mechanisms that determine when an agent should act autonomously versus loop in a human.
We're looking to connect them with an AI Engineer who has shipped complex, production-grade LLM systems - whether that's scaling LLM workflows, building multi-agent systems, designing evaluation infrastructure, or developing AI products for demanding production environments. In this role, you'd spend most of your time advancing the company's core AI infrastructure and the systems powering intelligent agents across enterprise use cases, working across continuous learning, agentic workflows, human-in-the-loop feedback, evaluation, and orchestration.
What You'd Be Doing- 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
What Our Client Is Looking For- 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
Don't meet every point on that list? Our client is open to exceptional engineers with unconventional combinations of skills and experience, so we'd still encourage you to apply.
Compensation & Benefits- Competitive base salary and meaningful equity
- Comprehensive health, dental, and vision coverage
- Flexible PTO
- Support for setting up a home workspace
- Office meals, snacks, and drinks
- Additional location-appropriate benefits
Working Environment This is a highly collaborative, fast-paced team with a strong emphasis on in-person collaboration.
