Customer Success Engineer

About Formant

At Formant, we're building the operating system for intelligent machines. Our mission is to unlock the full potential of robotics by making it effortless to manage, operate, and scale heterogeneous fleets—powered by AI. Our customers span autonomous cleaning, logistics, agriculture, and more. We're a small, agile team working on a big, tangible future: real-world AI in motion.

NOTE- This role is based in the San Francisco Bay Area. You MUST be willing to relocate.

We're hiring a Customer Success Engineer: a customer champion who brings AI capabilities into the messy, complex reality of production robotics environments. This isn't a role for someone who wants to perfect algorithms in isolation. You'll spend your time embedded with customers, understanding their operations, identifying where AI can transform their business, and building solutions that deliver measurable impact.

You'll be the bridge between our customers' operational challenges and our platform's AI capabilities. When a logistics company needs to predict maintenance issues across 200 robots, or an agriculture customer wants to optimize route planning with LLMs, you're the person who turns that business problem into a deployed solution.

You'll report to our Director, Customer Success Engineering and work closely with product engineering and go-to-market teams to ensure every customer deployment succeeds and that lessons learned improve our platform for everyone.

What You'll Do

Customer-First Deployment & Implementation

• Own end-to-end AI implementations for enterprise customers ($500k+ ARR), from initial discovery through production deployment and beyond
• Embed on-site with customers to deeply understand their robotics operations, workflow constraints, and business objectives
• Transform ambiguous customer requirements (like "we need our robots to work better") into concrete, deployed AI solutions that drive measurable ROI
• Build trust as the technical expert customers rely on during critical deployments and production issues

AI Solutions in Production Environments

• Design and implement LLM-powered workflows, RAG pipelines, and AI solutions tailored to each customer's specific robotic use cases
• Rapidly prototype solutions that balance cutting-edge AI capabilities with production reliability requirements
• Navigate the real-world constraints of robotics deployments: latency, connectivity, safety, and integration with existing systems
• Create reusable frameworks and tools that accelerate future customer deployments

Cross-Functional Impact

• Serve as the voice of the customer to product engineering, translating field insights into platform improvements and new AI capabilities
• Collaborate with go-to-market teams to demonstrate technical value in customer engagements and support expansion opportunities
• Enable customer teams through training, documentation, and knowledge