Remote AI Solutions Architect — US, 25% Travel

Insight Global; United States; Remote; USD 150,000 - 230,000; Full time

Job summary

Insight Global is seeking a Forward Deployed Engineer to scope, sell, and deliver enterprise AI solutions for Fortune 500 clients. This role combines client-facing solution architecture, pre-sales leadership, executive communication, and hands-on engineering.

The role requires 8–12 years of engineering delivery, deep experience with LLMs, RAG, and cloud platforms, plus production Python, Docker, and Kubernetes skills. Remote within the US with up to 25% travel.

Qualifications

• 8–12 years of engineering experience, including recent production AI/ML delivery.
• Hands-on experience with LLMs, RAG, fine-tuning, agents, evaluations, and guardrails.
• Strong Python skills and experience with AWS, Azure, or GCP.
• Experience with Docker, Kubernetes, modern data platforms, ML, and data engineering.
• Enterprise pre-sales, discovery, scoping, and SOW experience.
• Experience supporting Fortune 500 or regulated environments.

Responsibilities

• Lead technical discovery, solution design, executive workshops, and SOW development.
• Build AI prototypes, reference architectures, and production systems.
• Deliver agentic workflows, RAG solutions, multimodal pipelines, and MLOps infrastructure.
• Write production-grade Python and establish engineering standards.
• Integrate AI solutions with cloud, data, identity, and enterprise platforms.
• Present technical strategies and architecture decisions to executive stakeholders.

Skills

Executive communication

Pre-sales experience

Solution architecture

Client engagement

MLOps

Cloud platforms

Tools

Python

Docker

Kubernetes

AWS/Azure/GCP

Job description

Insight Global is seeking a Forward Deployed Engineer to scope, sell, and deliver enterprise AI solutions for Fortune 500 clients. This role combines client-facing solution architecture, pre-sales leadership, executive communication, and hands-on engineering.

The role requires 8–12 years of engineering delivery, deep experience with LLMs, RAG, and cloud platforms, plus production Python, Docker, and Kubernetes skills. Remote within the US with up to 25% travel.