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Build and operate production GenAI assistants and agents, including LLM/RAG microservices, agentic workflows, REST services, vector search, and AgentOps pipelines. Responsibilities include prompt engineering, evaluation, testing, observability, performance optimization, security, responsible AI controls, incident response, and cost reduction. Collaborate with product, data science, cloud, and security teams while mentoring peers on GenAI and LLMOps practices.
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
Qualifications
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
- Operational Excellence
- Own on-call runbooks, SLOs, and incident reviews; embed observability
- Enforce Responsible-AI guardrails, data-privacy controls, and vulnerability-management policies for AI Assistants and AI agents
- Enablement & Mentoring
- Coach full-stack and data-science peers on GenAI/LLMOps patterns; create internal workshops and tech blogs.
Qualifications
- 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 handson experience using PostgreSQL
- Experience with CI/CD pipelines and modern DevOps delivery practices
- Experience deploying and operating applications on cloudnative platforms
- Proficiency with Gitbased version control and collaborative development workflows
- Understanding of modern application architectures, cloudnative patterns, and security best practices
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Top Skills:
Agentic WorkflowsAi AgentsAWSAzureAzure Ai FoundryAzure OpenaiCi/CdClaude CodeCursorDevOpsFastapiGCPGenerative AiGitGithub CopilotJavaLarge Language ModelsMicrosoft CopilotPostgresPrompt EngineeringPythonReactRest ApisRetrieval-Augmented Generation (Rag)Spring BootTypescript
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