Applied AI Engineer - Agent
AI Tools
Tech Stack
Agent Workflow
Build and advance an autonomous Cofounder agent system. Design end-to-end agent improvements with multi-agent orchestration, memory architectures, RAG systems, function-calling, and evaluation frameworks. Integrate across business tools like Gmail, Slack, Notion, Linear.
About the Role
The General Intelligence Company of New York is hiring an Applied AI Engineer to push the boundaries of their Cofounder autonomous agent system. You will own core backend systems and applied LLM work, designing end-to-end agent improvements, constructing evaluation frameworks, and deploying LLM techniques to production. You will also enhance core infrastructure for job orchestration, memory management, and integrations across business tools.
Key responsibilities include designing end-to-end agent improvements, constructing evaluation frameworks, deploying LLM techniques to production, and enhancing core infrastructure for job orchestration, memory management, and integrations.
AI/ML focus: Prompt engineering, function-calling, retrieval, embeddings, evaluation design. RAG systems and hallucination reduction. Multi-agent orchestration and memory architectures.
Infrastructure: Redis, Postgres/Supabase, task queues (Celery/Arq/SQS). Observability platforms (Datadog, OpenTelemetry). Data integrations: Gmail, Slack, Notion, Linear, Google Workspace.
Requirements: 4+ years backend engineering experience, preferably Python. Hands-on production experience shipping LLM features. Demonstrated ability building evaluation harnesses and measurement systems. Distributed systems fundamentals.
Nice-to-haves: Agent framework experience. Production RAG implementation. Event-driven system design.
Salary: $250,000 - $300,000 + 0.3%-0.6% equity.
