Remote AI OS Architect for 6-Month Contract

Harvey Nash; Dallas (TX); Remote; USD 120,000 - 180,000; Full time

Job summary

Harvey Nash is seeking an experienced AI OS Engineer for a high-impact, 6-month contract to lead the architecture and integration of an AI Operating System—an orchestration framework for autonomous agents, multi-LLM routing, memory, tool execution, and local-to-cloud compute pipelines.

You will turn architectural blueprints into production-grade infrastructure, develop real-time evaluation frameworks, and optimize latency and compute costs in a remote US-based setting with potential extension.

Qualifications

• 5+ years of production software engineering experience, with 2+ years focused on building agentic frameworks, multi-agent orchestrations, or LLM infrastructure.
• Advanced proficiency in Python, TypeScript/Node.js, and modern async execution models.
• Hands-on expertise with agent architectures and orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI, LlamaIndex, or custom in-house runtimes).
• Proven track record working with vector databases, embedding systems, and hybrid RAG implementations.
• Direct experience with Docker, Kubernetes, vLLM / Triton inference engines, and cloud platforms (AWS Sagemaker, GCP Vertex AI, or Azure ML).
• Mastery of RESTful/gRPC APIs, message queues (Kafka, RabbitMQ, Redis), and microservice architectures.

Responsibilities

• Design, build, and deploy agentic workflows, dynamic task schedulers, and execution runtime environments powering internal AI applications.
• Implement robust retrieval systems, long-term state persistence, vector databases (e.g., pgvector, Qdrant, Pinecone), and hybrid-search mechanisms to optimize agent context windows.
• Architect multi-model routing layers (e.g., Anthropic, OpenAI, open-source foundation models) for cost-efficiency, fallback management, and low-latency inference.
• Develop secure sandbox environments for tool execution, code generation, API calls, and agent safety protocols.
• Build evaluation harnesses to track model drift, execution accuracy, hallucination rates, and latency bottlenecks.
• Containerize and deploy AI OS infrastructure on cloud environments (AWS / GCP / Azure) using CI/CD pipelines.

Skills

Python

TypeScript/Node.js

Async programming

LLM infra concepts

RESTful APIs / gRPC

Tools

Docker

Kubernetes

vLLM/Triton

AWS GCP Azure

Job description

Harvey Nash is seeking an experienced AI OS Engineer for a high-impact, 6-month contract to lead the architecture and integration of an AI Operating System—an orchestration framework for autonomous agents, multi-LLM routing, memory, tool execution, and local-to-cloud compute pipelines.

You will turn architectural blueprints into production-grade infrastructure, develop real-time evaluation frameworks, and optimize latency and compute costs in a remote US-based setting with potential extension.