Summary: Moreton Capital Partners seeks a Junior LLM / Agents Engineer to build production AI systems for accelerating research, trading, and decision-making in systematic commodities. Highlights: 1. Build production AI tools directly supporting live trading capital 2. Develop LLM-powered systems and RAG pipelines for research & trading 3. High ownership and rapid responsibility in a lean environment ### **Junior LLM / Agents Engineer – Systematic Commodities Hedge Fund** Moreton Capital Partners is seeking a Junior LLM / Agents Engineer to help build internal AI systems that accelerate research, trading, and decision\-making across our systematic commodities platform. We trade global commodity futures using machine learning and institutional\-grade infrastructure. A growing portion of our edge comes from automation: faster research workflows, better signal interpretation, and richer alternative data. This is not a “chatbot” role. You will be building production AI tools that directly support live trading capital. ### **What you will work on** * Internal research copilots that explain signals, model outputs, and portfolio positioning to traders and quants * Signal/model assistants that summarize why trades are firing and highlight changes in exposures or regime shifts * Automated news briefings that generate daily/real\-time summaries for commodities, macro, and sector\-specific events * News sentiment and event extraction pipelines to create structured features for ML models * Alternative data enrichment, turning unstructured text (news, reports, filings) into quantitative inputs * Natural\-language querying of internal databases (ask questions directly against signals, backtests, and risk data) * Workflow agents that automate repetitive research and ops tasks across Slack, Notion, Sheets, and internal tools * Integrations with tools such as Clawdbot, OpenAI/Claude APIs, LangChain, LlamaIndex, vector databases, and internal Python services ### **Key Responsibilities** * Design and deploy LLM\-powered systems embedded directly into research and trading workflows * Build RAG pipelines over proprietary research, backtests, signals, and documentation * Develop agents that call APIs, query databases, and automate multi\-step tasks * Convert unstructured text/news into structured features for quantitative models * Evaluate quality, latency, and cost of model pipelines * Productionize systems with monitoring, guardrails, and logging * Collaborate closely with quant devs and researchers to ship tools that save real time **Requirements** * Strong Python fundamentals * Experience using LLM APIs (OpenAI, Anthropic, or similar) * Familiarity with agent frameworks (LangChain, LlamaIndex, CrewAI, etc.) * Comfortable working with APIs, databases, and backend services * Practical builder mindset — able to ship useful tools quickly * Self\-starter who thrives in a lean, high\-ownership environment * Degree in CS/Engineering or equivalent hands\-on experience ### **Bonus Points For** * NLP or text analytics experience (sentiment, classification, embeddings) * Vector databases (Pinecone, Weaviate, Chroma, etc.) * Data engineering or backend experience * Exposure to markets, commodities, or systematic trading * Cloud (AWS), Docker, CI/CD **Benefits** * Performance bonus tied to firm growth and personal performance (up to 3x salary) * High ownership and rapid responsibility * Direct exposure to traders, quants, and live capital