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.

• 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
  

• 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

• 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
  

• 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

• 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