Forward Deployed AI Architect (On-Prem AI & Private Cloud)

Job Title: Forward Deployed AI Architect (On-Prem AI & Private Cloud)

Location: Remote
Duration: 6 Months

Job Description

We are seeking an experienced Forward Deployed AI Architect to lead enterprise AI deployments in customer environments. The ideal candidate will have extensive experience designing and implementing on-prem AI infrastructure, private cloud AI platforms, and production-grade Generative AI solutions. This is a highly client-facing architect role requiring hands-on experience delivering AI models and enterprise AI architecture from design through deployment.

Key Responsibilities

• Lead end-to-end deployment of enterprise AI solutions in customer on-prem environments.
• Design and implement scalable private AI infrastructure and private cloud architectures.
• Architect and deploy production-ready Generative AI platforms and AI model serving environments.
• Design and implement Retrieval-Augmented Generation (RAG) pipelines and advanced context engineering solutions.
• Develop AI model training pipelines, fine-tuning workflows, and model evaluation frameworks.
• Build model harnesses, inference pipelines, and deployment automation.
• Work directly with enterprise clients to gather requirements, design AI solutions, and lead technical implementation.
• Optimize AI infrastructure for security, scalability, and performance.
• Collaborate with cross-functional engineering teams throughout delivery.

Required Skills

• 10+ years of IT experience with significant experience in AI Architecture.
• Strong experience as a Forward Deployed AI Architect/Engineer or customer-facing AI Architect.
• Hands-on experience deploying AI solutions in on-premises environments.
• Expertise designing private AI architectures and private cloud platforms.
• Experience delivering enterprise AI models into production.
• Strong experience with RAG Engineering and Context Engineering.
• Experience with AI model training, fine-tuning, and model harness development.
• Experience with LLM deployment, inference optimization, and AI orchestration.
• Strong client communication and solution architecture skills.
• Ability to lead enterprise AI implementations from architecture through production deployment.