Support and implement end-to-end AI deployments for customers, from discovery through production rollout
Participate in on-site customer engagements (approximately 25–35% travel)
Work with external stakeholders to translate customer operational needs into technical requirements and working solutions
Troubleshoot and resolve production issues in collaboration with engineering
Help document best practices and implementation playbooks
Build and iterate on LLM-powered workflows, RAG pipelines, and AI-assisted automation tools
Prototype quickly while balancing reliability and performance
Integrate with customer systems and APIs
Navigate real-world physical constraints (latency, connectivity, hardware limitations)
Contribute reusable components that accelerate future deployments
Support existing external customers and resolve their potential issues
Partner with product engineering to relay field feedback and improve platform capabilities
Support technical conversations during customer engagements
Help enable customer teams through documentation and training materials
Contribute insights that shape product roadmap and deployment strategy

2–4 years in a customer-facing technical role (Solutions Engineering, Implementation Engineering, Technical Support Engineering, or similar)
Exposure to LLMs, prompt engineering, or AI/ML workflows (production experience a plus but not required) and appetite working with AI tools
Experience deploying technical solutions into production environments
Strong programming skills in Python or TypeScript
Comfortable working in ambiguity and learning new domains quickly
Willingness to travel for customer deployments (25–35%)
Experience integrating APIs and building full-stack solutions
Familiarity with React or SQL
Exposure to robotics or physical systems (ROS, AMRs, industrial automation, etc.)
Experience at a startup or in a fast-paced environment
Background working with operational or industrial customers

Forward Deployed Engineer, Customer Facing

Key skills