Artificial Intelligence Engineer Job at CNA Search in New York
CNA Search, New York, NY, United States
Most AI roles right now are experimentation.
This isn’t one of them.
We are looking for someone who has actually built and deployed AI systems into production . Not demos. Not notebooks. Real systems with users, failure modes, and performance constraints.
You will lead the design and delivery of agentic AI systems that need to operate reliably in enterprise environments.
What You’ll Own
Architecture and delivery of agent-based AI systems
End-to-end LLM pipelines including orchestration, tool use, and retrieval
Designing systems with memory, reasoning, and controlled execution
Translating unclear business problems into working AI systems
Setting technical direction across AI, backend, and infrastructure
Mentoring engineers and raising the bar on production quality
Core Requirements
8+ years building AI/ML or intelligent systems in production
Proven experience deploying LLM or AI systems beyond prototype stage
Strong experience with RAG, retrieval systems, and embeddings
Hands-on with agent frameworks (LangGraph, LangChain, AutoGen, CrewAI, etc.)
Strong Python experience building scalable systems
Experience designing systems, not just contributing to them
Cloud experience (AWS, GCP, or Azure)
Strong Signals
Built multi-agent systems with orchestration and coordination
Experience with memory systems, state handling, and retries
Designed guardrails, evaluation frameworks, or observability for AI
Worked on systems where reliability and failure handling mattered
#J-18808-Ljbffr
This isn’t one of them.
We are looking for someone who has actually built and deployed AI systems into production . Not demos. Not notebooks. Real systems with users, failure modes, and performance constraints.
You will lead the design and delivery of agentic AI systems that need to operate reliably in enterprise environments.
What You’ll Own
Architecture and delivery of agent-based AI systems
End-to-end LLM pipelines including orchestration, tool use, and retrieval
Designing systems with memory, reasoning, and controlled execution
Translating unclear business problems into working AI systems
Setting technical direction across AI, backend, and infrastructure
Mentoring engineers and raising the bar on production quality
Core Requirements
8+ years building AI/ML or intelligent systems in production
Proven experience deploying LLM or AI systems beyond prototype stage
Strong experience with RAG, retrieval systems, and embeddings
Hands-on with agent frameworks (LangGraph, LangChain, AutoGen, CrewAI, etc.)
Strong Python experience building scalable systems
Experience designing systems, not just contributing to them
Cloud experience (AWS, GCP, or Azure)
Strong Signals
Built multi-agent systems with orchestration and coordination
Experience with memory systems, state handling, and retries
Designed guardrails, evaluation frameworks, or observability for AI
Worked on systems where reliability and failure handling mattered
#J-18808-Ljbffr