Manager, Platform Engineering, AI & Data Science

Cargill’s size and scale allows us to make a positive impact in the world. Our purpose is to nourish the world in a safe, responsible and sustainable way. We are a family company providing food, ingredients, agricultural solutions and industrial products that are vital for living. 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 alternative fuel. Our 160,000 colleagues, operating in 70 countries, make essential products that touch billions of lives each day. Join us and reach your higher purpose at Cargill.

Job Purpose and Impact

The Manager for AI Platform Engineering leads the team that designs, builds, and operates Cargill’s enterprise AI-Ops platform—covering MLOps, LLMOps/GenAIOps, HPC scheduling, and optimisation services (e.g., Gurobi, RStudio Workbench). You will own the platform roadmap, allocate people and budget, drive project delivery, and embed best-in-class reliability, security, and compliance practices. Success is measured by platform uptime, model-to-production velocity, cost-to-serve trends, and team engagement.

Key Accountabilities

Platform Ownership & Road-mapping 

• Define and maintain the technical roadmap for MLOps, LLMOps, HPC, and optimization tooling 
• Oversee the portfolio of AI-Ops projects; align scope, schedule, and budget to business objectives. 

Technical Guidance & Governance 

• Champion infrastructure-as-code, GitOps, and CI/CD pipelines  

Quality, Reliability & Compliance 

• Set and monitor SLIs/SLOs for training, inference, and optimization services; lead post-incident reviews. 
• Ensure Responsible-AI guardrails, data-privacy, and license-management policies are implemented. 

Process Improvement & Automation 

• Drive continuous-improvement initiatives (test-driven development, auto-scaling policies, cost dashboards). 

Stakeholder & Customer Engagement 

• Partner with product managers, data-science leads, and security/compliance teams to capture requirements and set priorities. 

Team Management & Talent Development 

• Set performance objectives, conduct regular feedback and coaching sessions, and create growth plans. 
• Foster an inclusive culture that values experimentation, blameless post-mortems, and knowledge sharing

Qualifications

• Minimum requirement of 4 years of relevant work experience. Typically reflects 5 years or more of relevant experience.

Preferred: 

• 3+ years running production MLOps/LLMOps or HPC environments
• 2 + years managing engineers or cross-functional delivery teams

Equal Opportunity Employer, including Disability/Vet.