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Principal AI Engineer & AI Engineer | Agentic AI / LLM
Omiz Staffing Solutions (OSS)
2 hours ago
Full-time
On-site
New City, New York, United States
Hiring: Principal AI Engineer & AI Engineer | Agentic AI / LLM
Please ensure you read the below overview and requirements for this employment opportunity completely.
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 xsgimln 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.
Please ensure you read the below overview and requirements for this employment opportunity completely.
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 xsgimln 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.