Founding LLM Engineer (Visa Sponsorship)

Spherecast • San Francisco, CA

2d

About The Position

As a LLM Engineer at Spherecast, you will be responsible for building Agnes from the ground up – our AI Supply Chain Manager that decides what to produce, where to make it, and how to move it through factories, warehouses, and channels. This is a fast-paced, highly autonomous role for someone who can own AI systems end-to-end: from prototypes to production, from prompts to tested and evaluated pipelines, from agents to real-world outcomes (POs, TOs, bookings). You’ll work directly with the core team to turn the physical flow of goods into something as programmable as code. If you’re a builder who thrives at the intersection of LLMs, agents, systems engineering, and messy real-world data, this is your opportunity to shape how global brands run their supply chains.

Requirements

• Hands-on experience with modern LLM APIs (e.g. Anthropic, OpenAI, DeepSeek, OpenRouter, Gemini, Moonshot) and have shipped features using them.
• Strong intuition for large language model selection – understanding the strengths, weaknesses, latency/cost tradeoffs, and ideal use cases of different LLMs.
• Practical experience with the HuggingFace ecosystem in real projects.
• A track record of building LLM-powered automations or agents that are core to a production system, not just internal demos or playgrounds.
• Experience designing and maintaining evaluation pipelines to iterate quickly and safely on prompts and workflows.
• Strong prompting and system-design skills – designing tools/functions, structured outputs, and multi-step agent flows that are robust to edge cases.
• Experience with LLM observability and monitoring (logging, traces, quality metrics, feedback loops) to track and improve production accuracy over time.

Nice To Haves

• Experience running self-hosted LLMs in production or serious prototypes.

Responsibilities

• Building Agnes, the AI Supply Chain Manager, from the ground up.
• Owning AI systems end-to-end: from prototypes to production, from prompts to tested and evaluated pipelines, from agents to real-world outcomes (POs, TOs, bookings).
• Working directly with the core team to turn the physical flow of goods into something as programmable as code.
• Shaping how global brands run their supply chains.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed