AI Forward Deployed Engineer

About the team

The Artificial Intelligence Orchestration (AIO) team is responsible for how GILLIG puts artificial intelligence to work across the enterprise. We are committed to adopting AI thoughtfully and securely, growing the AI fluency of every organization we support, and delivering applications that make GILLIG faster, smarter, and easier to do business with. Our engineers are engaged in strategy, mentorship, and hands-on development across a wide range of business and technical areas, and the solutions we deliver serve both internal teams and external customers.

About the role

We are looking for an AI Forward Deployed Engineer to integrate with business stakeholders and own solutions from problem statement through production and ongoing support. The position blends application engineering and program management: you will define problems with stakeholders, evaluate potential solutions, and build, deliver, and maintain the applications that result. You will work with AI-accelerated development as your default mode, and the products you deliver may or may not contain AI; the mission is business impact through automation, new features, and new capability.

Responsibilities

• Work directly with stakeholders to identify and sharpen the problem statement before any solution is proposed
• Lead stakeholders through review of potential solutions and drive alignment on scope, success criteria, and timeline
• Build proofs of concept rapidly on the foundation team’s common template, working with the UX Engineer, Data Engineer, and AI Infrastructure Engineer
• Carry products from proof of concept to production: hardening, stakeholder acceptance, rollout, and training
• Act as program manager for your engagements: status, risks, stakeholder communication, and delivery accountability
• Iterate on shipped products as business needs evolve
• Maintain products for their life in service, leveraging the common template to keep the maintenance burden low
• Use AI-accelerated development (LLM coding tools running against the team’s templates) as your default build mode
• Support the team’s AI Fluency mission by mentoring stakeholder organizations on AI capabilities and proper usage during engagements
• Feed lessons from each engagement back into the foundation team’s templates, patterns, and playbooks

Requirements

• Bachelor of Science Degree in Engineering or Computer Science
• Minimum 2 years of experience in software or application engineering, including full-stack delivery of production applications
• Demonstrated stakeholder-facing experience: requirements discovery, solution reviews, and delivery communication with non-technical business partners
• Program or project management fundamentals, with the ability to run your own engagements: scope, schedule, risk, and status
• Strong proficiency in at least one of Python or TypeScript/JavaScript, with working range across the stack (front end, APIs, data)
• Hands-on experience with LLM-assisted development (e.g., Claude Code, Codex, OpenCode) and judgment about where it accelerates work and where it needs supervision
• Comfort with ambiguity; requirements and specifications will not exist until you create them with the stakeholder
• Prior forward deployed, solutions engineering, consulting, or internal-tools experience owning outcomes end to end preferred

Work environment

• Ability to lift 25 lbs
• Prolonged periods of sitting/standing at a desk and working on a computer
• Regularly required to sit, stand, and walk and occasionally kneel or squat
• The ideal candidate must be able to complete all physical requirements of the job with or without reasonable accommodation
• Must be able to navigate manufacturing environment, comfortable around heavy machinery, tools, etc.
• Must be able to wear Personal Protective Equipment (i.e. safety glasses, bump caps, hearing protection, etc.)
• 5% travel may be required
• Typical start time 7:00 AM PST (negotiable)

Pay

$140,000 - $180,000 annual salary + premium benefits

Pay offered may vary depending on multiple individualized factors, including market location, job classification, job-related knowledge, skills, and experience.