Principal, AI Platform Engineer
Cargill
Cargill is committed to providing food and agricultural solutions to nourish the world in a safe, responsible, and sustainable way. Sitting at the heart of the supply chain, we partner with farmers and customers to source, make and deliver products that are vital for living.
Our 155,000 team members innovate with purpose, providing customers with life's essentials so businesses can grow, communities prosper, and consumers live well. With over 160 years of experience as a family company, we look ahead while remaining true to our values. We put people first. We reach higher. We do the right thing—today and for generations to come.
Job Purpose and Impact
Come build the AI platform that engineers across Cargill will use every day—shipping low-code and pro-code AI agents that turn real problems into real outcomes. At Cargill, you're not optimizing vanity metrics; you're helping a global company that puts food on tables around the world deliver better, faster, safer decisions at massive scale. We're looking for engineers with integrity (do the right thing when no one's watching), hunger to learn (stay curious, test, iterate), and a builder mindset (prototype, harden, scale). You'll do well here if you move work forward even with dependencies, communicate clearly, and ship value in increments—building strong relationships while finding practical paths around blockers.
Key Accountabilities
- AI SOLUTION ARCHITECTURE: AI Solution Architecture: Designs and leads end to end AI platform solution design, establishing technical architectural patterns, designs&strategies.
- PLATFORM STRATEGY: defines the long-term platform and technology strategy for AI core capabilities across Cargill
- ADVISOR: Serves as a senior AI technology&thought leader, partnering with engineering, enterprise architecture, and information security to align AI platforms and architecture to overall architecture decisions and frameworks.
- PLATFORM OPERATIONS&GOVERNANCE: Defines and operates processes supporting SLAs/SLOs, including on-call readiness, incident response, runbooks, and multi-team contribution models.
- SECURITY&RISK MANAGEMENT: Defines platform-level safeguards against prompt injection, tool misuse, and data leakage, ensuring secure handling of data, models, and integrations, partnering closely with cyber security.
- STAKEHOLDER ENGAGEMENT: Partners with business and technical leaders to align AI technology strategies with strategic priorities, communicate outcomes, and drive adoption across teams.
- CI/CD&ENGINEERING EXCELLENCE: Establishes and enforces CI/CD pipelines with automated testing, evaluation gates, versioning, and safe release strategies to maintain production quality.
- MODEL&DATA ENGINEERING: Guides development and deployment of advanced models and RAG pipelines, ensuring strong evaluation, reproducibility, and performance monitoring.
- AGENTIC SYSTEM DESIGN: Architects robust agent workflows including structured outputs, tool orchestration, fallback strategies, and deterministic execution patterns.
Qualifications
- Minimum requirement of 6 years of relevant work experience. Typically reflects 10 years or more of relevant experience.
- 5 years building, maintaining enterprise scale platforms with scalability, reliability and performance
- 5+ years experience in a software engineering capacity
- 3 years of architecture experience
- Hands on experience with AWS and/or Azure cloud services (Bedrock, AI Foundry, containers),
- Devops/platform architecture and operations experience
- Python and or Go language (vibecoding is acceptable)
- Experience in developing agents/RAG in production (CI/CD)
PREFERRED SKILLS
- Experience designing and optimizing RAG systems including chunking strategies, embeddings, and retrieval evaluation techniques.
- Expertise in multi-model orchestration, routing strategies, and cost/performance trade-off optimization.
- Strong experience with AWS services including containers, IAM, networking, secrets management, and observability.
- Familiarity with LLM observability tools (traces, evals, datasets) for production monitoring and regression detection.
- Experience designing reusable tool ecosystems or MCP-style integrations with strong governance and auditability.
- Proficiency in infrastructure as code (Terraform or similar) and platform automation practices.
- Ability to develop architecture diagrams, technical blueprints, and communicate complex systems to diverse stakeholders.
Additional Details:
- Internal Title: Principal, AI&Data Sciences
- Location: GA-Atlanta
- The business will not sponsor applicants for work visas for this position
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Equal Opportunity Employer, including Disability/Vet.
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