Senior Software Engineering - Ag & Trading

Job Purpose and Impact

The Senior Software Engineering - Ag & Trading for AI Assistants & Agents in AI & Data Science builds services to operate Cargill's portfolio of GenAI Assistants and Agents - including ChatGPT-powered copilots and bespoke LLM services. You will translate product requirements into secure, efficient, and observable services and or agents; manage the lifecycle from experiment to production; and continually improve reliability, latency, and cost. Typical deliverables span REST services, vector-search back end, LLMOps & AgentOps pipelines, and rich front-end components for knowledge workers and plant operators. Expect to collaborate daily with product managers, data scientists, cloud engineers, and security teams while acting as the technical authority for GenAI feature design and launch.

Key Accountabilities

• Design & Build
  • Develop multi-agent workflow automation patterns using Agentic AI
  • Process redesign and mapping to agentic workflow patterns
  • Architect scalable micro-services that wrap LLM/RAG/Agent workflows (Python).
  • Implement robust prompt-engineering patterns, retrieval pipelines, and caching for AI Assistants and AI Agents
• Platform Ops

• Extend evaluation, automated testing, canary rollout, and rollback for AgentOps.
• Profile inference latency, GPU/CPU utilization, and memory; deliver quarterly cost-to-serve reductions
• Lead bug-fix, security-patch, and performance-tuning sprints for live AI Assistants and AI Agents

• Minimum: 4 years building production software or data platforms .
• Typical: 5-8 years, including 2+ years with cloud-native AI/ML or GenAI systems (Azure, AWS, or GCP) or 2+ years of software devlopment
• Experience building and scaling full-stack applications using the following languages/frameworks: React & typescript, Java (Spring Boot) and/or Python
  Preferred:
  
  • Experience building AI solutions, working with AI tools like Claude Code, GitHub Copilot, etc.
  • Experience with building applications that use large language models or other AI services
  • Working with AI coding assistants or agentic development tools
  • Strong foundation in relational databases, with hands‑on experience using PostgreSQL
  • Experience with CI/CD pipelines and modern DevOps delivery practices
  • Experience deploying and operating applications on cloud‑native platforms
  • Proficiency with Git‑based version control and collaborative development workflows
  • Understanding of modern application architectures, cloud‑native patterns, and security best practices