Software Engineer-AI

Job Purpose and Impact

The Software Engineering Professional will lead the design build and ongoing support of AI Assistants AI Agents and automation solutionsleveraging ChatGPTbased copilots Copilot-Studio-Onboarding--Building-Testing-and-Deploying-AI-Agents-for-Maximum-Value-at-Cargill agents and Power Automate workflowswhile adhering to AI CoE platform standards and guardrails. Deliverables typically span API and integration services retrieval and vector-search pipelines LLMOps/AgentOps operational tooling and intuitive front-end experiences for both office users and plant role will work primarily within our Food EMEA Digital Technology and Data team and assist with solutions for our technology stack servicing our Food EMEA team and this role youll have a strong partnership with the business Product Owner with an emphasis on translating product requirements into secure efficient and observable services or agents manage the lifecycle from experiment to production; and continually improve reliability latency and cost. You will work as part of a product team to ensure the digital products outputs of the team maximize value and drive efficiency consistency and digitally connected experiences for commercial teams and customers. Expect to collaborate outside of the product team with other product managers AI Center of excellence cloud engineers and security teams across the digital and technology and data ecosystem.

Key Accountabilities

• 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
• Profile inference latency GPU/CPU utilization and memory
• Writes and maintains highly complex unit tests and integration tests and performs debugging to maintain the quality and performance of the software/AI solutions
• Lead bug-fix security-patch and performance-tuning sprints for live AI Assistants and AI Agents
• Leads the establishment and maintenance of comprehensive documentation for agents applications deployment processes and system configurations.
• Own on-call runbooks SLOs and incident reviews; embed observability
• Leads and mentors technical support and troubleshooting for highly complex issues with deployed applications to ensure minimal downtime and fast resolution.
• Leads cross functional team of engineers to gather requirements and deliver solutions that meet business needs.
• Experience working within product and agile delivery frameworks including backlog management and cross-functionality delivery and full E2E engineering.
• Experience with enterprise architecture data governance or security standards in the context of digital solution deliveryas part of E2E engineering and solution architecture.
• Experience with digital technologies in the commercial & sales management capability (e.g. Salesforce Service Cloud CPQ Salesloft ChatGPT or similar platforms)

Qualifications

• Minimum requirement of 2 years of building production software or data platforms.
• Typically reflects 3 years or more with 2 years of cloud-native AI/ML or GenAI systems (Azure AWS or GCP) or 2 years of software development.