Job Purpose and Impact

• The Senior Professional, AI & Data Science job plans and leads the development of artificial intelligence models from design and prototyping through deployed solutions to drive decision making. With minimal supervision, this role extracts and integrates complex data from various sources, builds advanced models suitable for the business use case and evaluates model performance for accuracy, scaling and deployment. This job also develops compelling and clear communication materials to facilitate partner on board.
• 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 DEVELOPMENT: Designs and delivers end-to-end AI solutions from concept to production using Python, integrating LLMs, RAG pipelines, and structured agent workflows.
• PLATFORM INTEGRATION: Builds and operates solutions on a multi-team AI platform, leveraging shared services such as LLM gateways, vector stores, and tool ecosystems.
• CI/CD & QUALITY: Implements CI/CD pipelines with automated testing, evaluation checks, and safe deployment practices to ensure reliable and repeatable releases.
• DATA & MODEL ENGINEERING: Prepares and integrates complex datasets, applies feature engineering, and evaluates model and retrieval performance for accuracy and scalability.
• AGENTIC WORKFLOW DESIGN: Develops robust agent behaviors including tool calling, retries, guardrails, and deterministic outputs aligned to business requirements.
• OPERATIONS & RELIABILITY: Applies telemetry-first practices (logs, metrics, traces), supports on-call readiness, and maintains runbooks to meet defined SLAs/SLOs.
• SECURITY & GOVERNANCE: Implements secure-by-default practices including secrets management, access control, and protections against prompt injection and data leakage.

Qualifications

• Minimum requirement of 7 years of relevant work experience.
• PREFERRED SKILLS
• Experience designing AI solutions using RAG patterns including chunking, embeddings, and retrieval evaluation.
• Familiarity with multi-model orchestration, routing, and cost/latency optimization strategies.
• Experience with AWS services including containers, IAM, networking, and observability tooling.
• Exposure to LLM observability tools (traces, evals, datasets) for debugging and quality monitoring.
• Experience building reusable tool interfaces or MCP-style integrations for agent ecosystems.
• Ability to create solution diagrams, workflows, and technical blueprints with stakeholders.
• Familiarity with infrastructure as code and environment promotion strategies in CI/CD pipelines.