Applied AI Engineer - Agent

The role

You will own core backend systems and applied LLM work to advance agent reliability and autonomy. You will design agent improvements, build evaluation pipelines, and productionize LLM techniques.

What you will do

• Design and implement agent improvements end-to-end
• Build robust evaluation pipelines for the agent
• Productionize applied LLM techniques
• Improve core backend systems
• Partner with product and infra to define success metrics and ship fast, safe iterations
• Write clean, well-tested code
• Document design decisions and runbooks

Required qualifications

• 4+ years backend engineering experience
• Hands-on LLM experience: prompt engineering, function-calling, retrieval, embeddings, evaluation design
• Shipped LLM features to production
• Track record building evaluation harnesses and using them to drive improvements
• Solid distributed systems fundamentals: concurrency, reliability, performance, data modeling, lifecycle management
• Pragmatic experimentation: hypothesis to prototype to measured improvement to rollout
• Excellent debugging and instrumentation skills

Nice to have

• Experience with agent frameworks, tool orchestration, and memory architectures
• RAG systems in production (chunking, retrieval quality, freshness strategies)
• Redis, Postgres/Supabase, queues (e.g., Celery/Arq/SQS), and event-driven designs
• Observability stacks (Datadog, OpenTelemetry), and cost/latency optimization

Benefits

• Competitive salary
• Meaningful equity
• Comprehensive benefits
• Flexible work setup

About the company

generalintelligencecompany aims to build autonomous agents that run entire businesses.