6897 - AI Solutions Engineer

Reporting to the Director of Digital Product Management, you will prototype, launch, and scale user-facing agentic workflows and solutions that deliver measurable value across Conagra’s commercial organization. You will turn business use cases into working pilots, iterate with partners, and move the right solutions into production. 

Your Impact 

• Build and ship fast: Prototype, iterate, and take to production multi-step agentic workflows that solve real business tasks such as information gathering, trend synthesis, and opportunity sizing. Translate use cases into clear flows using platform building blocks and connectors and deliver grounded outputs with citations. 

• Own the experience: Design prompts and task flows and create simple chat or UI surfaces where needed. Integrate results back into business systems. Write clean, maintainable code, and optimize application latency, reliability, and cost. 

• Shape the build plan: Contribute to a practical generative AI backlog with AI Strategy, sequence work, and de-risk ideas with quick proofs before scaling. 

• Ground outputs in data: Use retrieval over governed sources. Design prompts and simple checks so answers are accurate, attributable, and include citations. 

• Validate and raise quality: Build simple evaluation tests for each task, monitor task success and citation coverage, catch hallucinations and data leakage, and fix regressions quickly. 

• Partner with the platform team: Build reusable agentic solutions on shared tooling, maintain end-to-end observability with traces, logs, and metrics, and meet weekly with IT on a shared backlog to align priorities and shape the platform roadmap. 

• Lead with code: Drive projects end to end. Write production-quality code, review pull requests, and set engineering standards. 

• Partner to production: Work with Data Engineering, Platform Engineering, IT Enablement, and product and business partners to move pilots to scale with clear SLAs and handoffs. 

• Document and enable reuse: Publish patterns, components, and starter projects so new pilots launch faster. 

• Stay current and pragmatic: Track useful advances in Large Language Model (LLM) tooling and retrieval and adopt improvements that demonstrably help outcomes. 

Your Experience 

• 5+ years of experience. 

• Education: Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or a related field, or equivalent practical experience. 

• Proven experience leading AI projects end to end with hands-on software engineering and code development, from prototype to production. 

• Proficiency in Python and at least one of Java, TypeScript/JavaScript, or C# (.NET). 

• Shipped at least one AI application that uses retrieval over enterprise data with citations. 

• Hands-on with agent frameworks such as Semantic Kernel, LangGraph, or LangChain, composing tools and functions into multi-step workflows.<