Job Purpose and Impact
The Senior AI Consultant will design, build and scale generative-AI agents that automate and augment trading and analyst workflows, generating strategic insights that promote the company's competitive position and ultimately grow trading earnings. In this role, you will partner across product lines to identify high-value agentic use cases, evaluate new data sources and tools, and implement reusable, well-governed agents and the interfaces around them. You will act as a link between trading / analyst teams and the broader GenAI capability, ensuring agents are consistent, reliable and token-efficient.
Key Accountabilities
- Design, build, test and deploy GenAI agents and copilots for trading and analyst workflows (prompting, loops, tool / function calling, orchestration).
- Validate quality and coverage of datasets and prioritize and implement generally defined data and analytical tool development efforts based on trading opportunity.
- Establish and reuse consistent agent design patterns, components and standards to avoid duplicated effort, uneven quality and inefficient token usage.
- Redesign workflows and processes around agents to maximize adoption, efficiency and measurable business impact.
- Build evaluation, monitoring and guardrails for agents to ensure reliability, safety and responsible-AI compliance.
- Create a culture of documenting best practices for building and using our core agent and GenAI platforms and capabilities, and upskill trading / analyst teams on using and building agents.
- Independently solve moderately complex issues with minimal supervision, while escalating more complex issues to appropriate staff.
- Other duties as assigned
Qualifications
MINIMUM QUALIFICATIONS
- Bachelor's degree in a related field or equivalent experience
- Experience applying business requirements and serve as a consultant to internal teams
- Knowledge of agricultural trading business and an understanding of the information that adds value to trading
- Experience with, and understanding of, relational and distributed data systems
- Experience using data visualization applications to develop and deploy insights and reporting
- Minimum requirement of 2 years of relevant work experience. Typically reflects 3 years or more of relevant experience.
- Demonstrated experience building generative-AI applications or agents (prompt engineering, RAG, tool / function calling)
PREFERRED QUALIFICATIONS
- Ability to develop queries using multiple programming languages
- Familiarity with scientific programming languages
- Understanding of commodity trading markets
- Minimum of five years of experience running data or data warehousing systems
- Hands-on experience building and deploying LLM-powered agents and copilots in production
- Proficiency with agent frameworks and orchestration (e.g., LangChain / LangGraph, function calling, MCP)
- Experience with major LLM platforms (Anthropic Claude, OpenAI, AWS Bedrock, , Snowflake Cortex,)
- Strong Python skills
- Experience with agent evaluation, guardrails and responsible-AI practices
- Familiarity with trading or analyst workflows and how to redesign them around AI
- Strong stakeholder communication and ability to translate business problems into agentic solutions
