Forward-Deployed AI Engineer, Energy & Hardware

What you will do

• Embed with a customer team, often on-site, and own delivery end to end: discovery, technical scoping, system design, build, and production rollout.
• Drive solutions from a 0 to 1 prototype through MVP to scale, writing and reviewing production-grade code across the stack.
• Build the hard parts hands-on: agents and sub-agents, MCP servers, RAG pipelines, evals, and integrations against real systems of record.
• Be the primary technical owner of the engagement, partnering with the customer's engineers, domain experts, and leadership.
• Codify what works into reusable building blocks, playbooks, and repeatable deployment patterns.
• Bring the field back to product: surface deployment friction and eval-driven signal that sharpens what gets built next.
• Integrate with devices, telemetry, and IoT pipelines, and design for real-world reliability at the edge.

What we are looking for

• 4 to 10 years of engineering experience, ideally customer-facing or in deployment; former founders welcome.
• You write and review production-grade code across frontend and backend, with Python as a baseline and TypeScript a strong plus.
• Hands-on production experience with LLMs: prompt engineering, agent development, evals, RAG, and deployment at scale.
• A track record of scoping and shipping complex systems, and comfort with cloud, data pipelines, and enterprise environments.
• High agency and comfort with ambiguity: you turn vague business problems into concrete technical plans and own the outcome.
• Strong communication and stakeholder management, from technical discovery to the executive relationship.
• Interest or experience in energy, IoT, hardware, or embedded systems.

Nice to have

• Experience with IoT, telemetry, embedded systems, or edge deployments.