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Be an Early Applicant
Reimagining what's possible for food and agriculture
The Role
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.
Summary Generated by Built In
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
Skills Required
- At least 4 years building production software or data platforms
- Typically 5–8 years of experience, including 2+ years with cloud-native AI/ML or GenAI systems, or 2+ years of software development
- Experience building and scaling full-stack applications using React and TypeScript, Java with Spring Boot, and/or Python
- Experience building AI solutions or applications using large language models or other AI services
- Experience with AI coding assistants or agentic development tools, such as Claude Code or GitHub Copilot
- Strong relational database foundation and hands-on PostgreSQL experience
- 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
What the Team is Saying
Gaby
Data Engineering Lead
Landon
North America Service Assurance Manager
Navita
Software Engineering Senior Supervisor
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William Orgertrice
Data Engineer
Kayode D.
Principal Data Engineer
Patricia
Supply Chain Learning & Development and Digital Support Lead
Heather W.
Software Engineer
Kristen K.
Factory of the Future Digital Product Manager
Shrey B.
Senior Software Engineer
Madhuri P.
Senior Data Scientist
William Orgertrice
Data Engineer — Data Function, Platforms and Product Engineering
Navita S.
Software Engineering Senior Supervisor
Heather W.
Software Engineer
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Cargill Compensation & Benefits Highlights
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Healthcare Strength — Health coverage includes comprehensive medical, dental, and vision options, with broad networks, mental-health/EAP resources, and wellness incentives. Feedback suggests plan choice and advocacy resources provide strong support for navigating care.
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Retirement Support — Retirement programs feature a 401(k) with company matching alongside an ESOP and an additional retirement account. Feedback suggests these elements are widely regarded as a strong long‑term value.
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Leave & Time Off Breadth — The published PTO structure scales from 15 to 30 days with tenure, alongside paid holidays and paid family leave. Feedback suggests the breadth of time off supports work‑life needs, especially for longer‑tenured employees.
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The Company
What We Do
We are a family company providing food, ingredients, agricultural solutions and industrial products to nourish the world in a safe, responsible and sustainable way. We connect farmers with markets so they can prosper. We connect customers with ingredients so they can make meals people love. And we connect families with daily essentials— from eggs to edible oils, salt to skincare, feed to flooring. By providing customers with products that are vital for living, we help businesses grow, communities prosper and consumers live well in their daily lives.
Why Work With Us
The decision to join Cargill can open the door to a world of possibility. As part of our Digital, Technology & Data team, you’ll get to be part of a large and diverse group full of unique perspectives united by a common, higher purpose while building a rewarding career full of opportunity, growth and the satisfaction of knowing your work matters.
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Cargill Teams
Cargill Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Typical time on-site:
Not Specified
