Role overview
LLM Engineer – Agnes
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.
What We’re Looking For
You are a great fit if you have:
- 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 – you understand 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 – you know how to design 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.
- Bonus: Experience running self-hosted LLMs in production or serious prototypes.