Forward Deployed AI Engineer

Nickerson Talent Solutions; Denver (CO); On-site; USD 150,000 - 230,000; Full time

Job summary

Nickerson Talent Solutions in Denver seeks a senior technologist for a client-facing role focused on systems architecture, deployment strategy, and large-scale technical implementations.

You will define deployment playbooks, drive ROI, and travel 25–50% with executives to prioritize opportunities. Collaborate with engineering, product, and commercial teams to scale delivery, and produce field-grounded reference materials using AI while ensuring accuracy.

Qualifications

• 7+ years of experience in a client-facing technical role focused on systems architecture, deployment strategy, customer success engineering, or large-scale technical implementations.
• Proven track record of delivering $1M+ demonstrable ROI on one or more projects.
• Deep technical proficiency in AI, IoT, Industrial systems, or Cloud.
• Uses AI daily in work and personal life.
• Top 10% communicator - equally effective from the shop floor to the boardroom.

Responsibilities

• Define and refine scalable deployment patterns and playbooks that reduce friction, improve repeatability, and maximize customer ROI.
• Serve as a trusted advisor to customer and partner executives, traveling alongside them 25-50% of the time to help prioritize opportunities based on impact, constraints, and opportunity cost.
• Own success frameworks and KPIs that clearly define "value delivered" across deployments and build mechanisms that drive adoption and expansion.
• Partner closely with Field Deployment Engineers (FDEs), engineering, product, and commercial teams to translate real-world deployment learnings into scalable delivery systems and requirements.
• Shape how proven deployments are explained externally by producing field-grounded reference materials - blogs, white papers, use cases, customer stories, and playbooks - using AI to generate consistent artifacts quickly, then refining them with expert judgment and real-world validation.
• Identify and eliminate failure modes and friction points across the delivery process by continuously improving playbooks, instrumentation, and execution standards.
• Operate in an AI-native way: leverage AI tools to synthesize deployment insights, build reusable artifacts, and accelerate iteration - while ensuring all patterns and guidance remain accurate, grounded, and consistent.

Skills

System architecture

Deployment strategy

AI/IoT/Cloud

Customer ROI

Executive communication

Job description

Key Requirements

• 7+ years of experience in a client-facing technical role focused on systems architecture, deployment strategy, customer success engineering, or large-scale technical implementations.
• Proven track record of delivering $1M+ demonstrable ROI on one or more projects.
• Deep technical proficiency in at least one of the following: AI, IoT, Industrial systems, or Cloud.
• Uses AI daily in both work and personal life.
• Top 10% communicator - equally effective from the shop floor to the boardroom.

What You’ll Do

Define and refine scalable deployment patterns and playbooks that reduce friction, improve repeatability, and maximize customer ROI. Serve as a trusted advisor to customer and partner executives, traveling alongside them 25-50% of the time to help prioritize opportunities based on impact, constraints, and opportunity cost. Own success frameworks and KPIs that clearly define "value delivered" across deployments and build mechanisms that drive adoption and expansion. Partner closely with Field Deployment Engineers (FDEs), engineering, product, and commercial teams to translate real-world deployment learnings into scalable delivery systems and requirements. Shape how proven deployments are explained externally by producing field-grounded reference materials - blogs, white papers, use cases, customer stories, and playbooks - using AI to generate consistent artifacts quickly, then refining them with expert judgment and real-world validation. Identify and eliminate failure modes and friction points across the delivery process by continuously improving playbooks, instrumentation, and execution standards. Operate in an AI-native way: leverage AI tools to synthesize deployment insights, build reusable artifacts, and accelerate iteration - while ensuring all patterns and guidance remain accurate, grounded, and consistent.