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
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Internal research copilots that explain signals, model outputs, and portfolio positioning to traders and quants
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Signal/model assistants that summarize why trades are firing and highlight changes in exposures or regime shifts
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Automated news briefings that generate daily/real-time summaries for commodities, macro, and sector-specific events
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News sentiment and event extraction pipelines to create structured features for ML models
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Alternative data enrichment, turning unstructured text (news, reports, filings) into quantitative inputs
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Natural-language querying of internal databases (ask questions directly against signals, backtests, and risk data)
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Workflow agents that automate repetitive research and ops tasks across Slack, Notion, Sheets, and internal tools
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Integrations with tools such as Clawdbot, OpenAI/Claude APIs, LangChain, LlamaIndex, vector databases, and internal Python services
Key Responsibilities
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Design and deploy LLM-powered systems embedded directly into research and trading workflows
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Build RAG pipelines over proprietary research, backtests, signals, and documentation
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Develop agents that call APIs, query databases, and automate multi-step tasks
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Convert unstructured text/news into structured features for quantitative models
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Evaluate quality, latency, and cost of model pipelines
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Productionize systems with monitoring, guardrails, and logging
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Collaborate closely with quant devs and researchers to ship tools that save real time
Requirements
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Strong Python fundamentals
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Experience using LLM APIs (OpenAI, Anthropic, or similar)
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Familiarity with agent frameworks (LangChain, LlamaIndex, CrewAI, etc.)
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Comfortable working with APIs, databases, and backend services
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Practical builder mindset — able to ship useful tools quickly
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Self-starter who thrives in a lean, high-ownership environment
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Degree in CS/Engineering or equivalent hands-on experience
Bonus Points For
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NLP or text analytics experience (sentiment, classification, embeddings)
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Vector databases (Pinecone, Weaviate, Chroma, etc.)
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Data engineering or backend experience
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Exposure to markets, commodities, or systematic trading
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Cloud (AWS), Docker, CI/CD
Benefits
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Performance bonus tied to firm growth and personal performance (up to 3x salary)
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High ownership and rapid responsibility
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Direct exposure to traders, quants, and live capital
