AI Developer

SCOPE

The AI Developer designs, builds, and deploys AI-powered solutions, automation workflows, and integrations that support HeartlandFPG business objectives. Working under the direction of the AI Architect, this role translates approved AI use cases from the intake process into functional, production-ready applications. The AI Developer is a hands-on technical contributor who partners with the AI Architect and AI Administration to operationalize the company's AI platforms and deliver measurable value to functional business units.

KEY RESPONSIBILITIES

Solution Development & Deployment

• Design, build, test, and deploy AI agents, automation workflows, and integrations on approved platforms (primarily Abacus.AI).
• Translate approved AI use cases and requirements into functional, production-ready solutions.
• Build and deploy AI agents and automations for CPG use cases such as promotional lift analysis, demand planning support, and retail execution across HeartlandFPG brands.
• Develop prompts, configurations, and supporting logic in line with the department's prompt engineering and AI integration standards.
• Build integrations between AI platforms and enterprise data sources, respecting governed data access controls.
• Document solution designs, configurations, and deployment steps to support maintainability and knowledge transfer.

Technical Operations & Support

• Monitor deployed AI solutions for performance, reliability, and accuracy; troubleshoot and resolve issues.
• Maintain and enhance existing AI solutions as business needs and platform capabilities evolve.
• Integrate AI solutions with the enterprise data ecosystem (ERP/SAP, Microsoft Fabric) in partnership with Information Technology (IT).
• Support user onboarding, access provisioning, and training in coordination with AI Administration.
• Participate in testing and validation of AI outputs per SOP-005 (AI Agent Output Review and Human Validation).

Collaboration & Governance

• Work under the technical direction of the AI Architect, escalating architectural and security decisions as appropriate.
• Partner with Functional Data Analysts to understand business requirements and deliver fit-for-purpose solutions.
• Develop solutions that respect food industry regulatory, labeling, and FDA (Food and Drug Administration) compliance data requirements.
• Ensure all development complies with the Enterprise AI Usage Policy V1 and applicable data privacy and security standards.
• Contribute to the AI tool inventory, reusable components, and best-practice documentation.

PHYSICAL DEMANDS

• Must be able to sit for extended periods of time and interact with computers, telephone and other electronic media. Overtime hours may be required to meet project deadlines.
• Overtime hours may be required to meet project deadlines.

QUALIFICATIONS

• Bachelor's Degree in Computer Science, Software Engineering, Data Science, or related field required.
• 3+ years of experience building software, automation, or AI/ML solutions in a business environment.
• Hands-on experience developing on AI or automation platforms; familiarity with enterprise AI platforms (e.g., Abacus.AI) preferred.
• Proficiency with programming/scripting (e.g., Python, SQL) and API-based integrations.

PERSONAL ATTRIBUTES

• Strong problem-solving skills and attention to detail.
• Self-motivated, accountable, and able to work both independently and collaboratively.
• Effective written and verbal communication; able to explain technical concepts to non-technical partners.
• Commitment to responsible, secure, and policy-compliant AI development.
• Ability to manage multiple priorities, work independently and collaboratively, and deliver results under pressure.

KNOWLEDGE & EXPERIENCE

• Experience deploying and maintaining production applications or automation workflows.
• Understanding of prompt engineering, large language models, and AI agent design patterns.
• Familiarity with data quality, security, and governance considerations in AI solution delivery.
• Experience integrating with enterprise data environments (e.g., Microsoft Fabric) is a plus.