Principal AI Engineer & AI Engineer | Agentic AI / LLM

🚀 Hiring: Principal AI Engineer & AI Engineer | Agentic AI / LLM We’re looking for hands-on AI Engineers and Staff/Principal-level AI Engineers to build and productionize next-generation Agentic AI and Generative AI solutions for enterprise environments. These are engineering-heavy roles for candidates who have actually built and deployed LLM/Agentic AI systems into production — not just prompt engineering, research, or basic chatbot/API integrations. 📍 Location: New York City, NY — Hybrid, 3 Days Onsite/Week 🕐 Work Hours: EST overlap required 💼 Roles Principal AI Engineer • 8–14 years software engineering experience • 10+ years preferred • 2+ years hands-on LLM/GenAI engineering • H-1B transfer candidates can be considered AI Engineer • Strong hands-on Python • 5+ years AI/ML/GenAI experience • Strong production AI/LLM engineering experience • Overall years of experience are flexible for strong AI candidates 🔥 Key Technical Skills AI / LLM / Agentic AI: Generative AI / LLMs Agentic AI & autonomous agents Agent orchestration Tool calling / Function calling MCP / Model Context Protocol LangGraph, CrewAI, Google ADK, Claude Agent SDK or equivalent RAG: RAG architecture Document ingestion & chunking Embeddings Vector & hybrid search Retrieval & reranking Context management Response validation Pinecone, Milvus, Weaviate, FAISS or equivalent Engineering: Strong Python APIs & microservices Distributed systems Backend engineering Data pipelines System design Evaluation & Reliability: LLM evaluation Regression testing AI observability & tracing LangSmith / Langfuse Guardrails Validators & fallback mechanisms AI reliability engineering Cloud / DevOps AWS — EKS/ECS, Lambda, S3, DynamoDB, Redshift, Step Functions, Bedrock Docker / Kubernetes Terraform / CloudFormation CI/CD Azure / GCP 🎯 What We're Looking For We want engineers who can demonstrate real production ownership, including: ✅ Built and deployed production LLM applications ✅ Built production Agentic AI systems ✅ Strong RAG implementation experience ✅ Hands-on MCP and tool-calling experience ✅ Strong Python engineering ✅ Experience with embeddings, chunking & vector databases ✅ Experience optimizing AI systems for latency, cost and token usage ✅ Ability to own AI systems end-to-end Profiles focused primarily on prompt engineering, academic research, basic chatbots, or simple LLM API integrations are not the target for these positions. Show more Show less