GenAI Forward-Deployed Engineer — Enterprise Impact

Deloitte France; Pittsburgh (Allegheny County); On-site; USD 135,000 - 265,000; Full time

Job summary

Deloitte's Forward Deployed Engineers (FDE) in the United States seek a skilled ServiceNow engineer to rapidly prototype and deliver GenAI-enabled solutions for enterprise clients. You will collaborate with senior client teams to translate business needs into actionable AI products, building production-ready code and scalable workflows.

The role emphasizes fast delivery, strong engineering practices, and mentoring teammates within an FDE pod.

Qualifications

• Bachelor's degree in Computer Science, Data Science or Engineering.
• 3+ years of software/analytics engineering experience.
• 1+ years building GenAI/LLM solutions in client or production environments.
• 1+ years leading project workstreams and translating problems into AI solutions.
• 1+ years of reliable, well-documented code development.

Responsibilities

• Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
• Partner with leaders and engineers to align priorities and delivery.
• Lead sessions to shape solutions and drive client outcomes.
• Prototype and deliver AI solutions using industry expertise and emerging capabilities.
• Contribute within an FDE pod and mentor newer team members.
• Build AI-enabled solutions, scalable patterns, and human-in-the-loop controls.
• Deliver production-quality code with testing, CI/CD, logging and documentation.

Skills

Software engineering

GenAI

Client engagement

Project leadership

Cloud familiarity

Education

Bachelor's degree in CS/Engineering/Data Science

Tools

ServiceNow

Claude Code

GitHub

Now Assist

Job description

Deloitte's Forward Deployed Engineers (FDE) in the United States seek a skilled ServiceNow engineer to rapidly prototype and deliver GenAI-enabled solutions for enterprise clients. You will collaborate with senior client teams to translate business needs into actionable AI products, building production-ready code and scalable workflows.

The role emphasizes fast delivery, strong engineering practices, and mentoring teammates within an FDE pod.