Forward Deployed Engineer

Insight Global; United States; Remote; USD 180,000 - 260,000; Full time

Benefits offered by this job

Remote in US

Travel 25%

Job summary

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

Responsibilities include leading discovery, building prototypes and production systems, and presenting strategies to executives. Strong Python, cloud, MLOps, and enterprise experience are required.

Qualifications

• 8–12 years of engineering experience with recent AI/ML delivery.
• Hands-on with LLMs, RAG, fine-tuning, agents, evaluations, guardrails.
• Enterprise pre-sales, discovery, scoping, and SOW experience.

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.

Skills

Solution architecture

Client facing

Python

LLMs

MLOps

Cloud platforms

Tools

Docker

Kubernetes

AWS/Azure/GCP

Job description

Remote- Must live in the US and be comfortable with 25% travel

A boutique AI consulting firm is seeking a Forward Deployed Engineer to help 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.

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.

Required Qualifications:

• 8 to 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.