AI Engineer

FIT Solutions•San Marcos, CA
•$100,000 - $120,000•Onsite

About The Position

The Manager, AI & Business Transformation leads Fresh Origins’ AI program from the business side. This is a business analyst and project manager first: someone who can sit with Operations, Sales, Accounting, and Production, understand how work actually gets done, find where AI and automation will pay off, and then run the projects that deliver it. The core of the role is AI program leadership: building the roadmap, managing outside AI partners, running pilots, driving adoption of the company’s enterprise AI tools, and reporting results to leadership and corporate. Supporting that is business analytics and reporting: defining KPIs, partnering with the analytics team on the company data lake and Power BI, and making sure decisions run on one trusted set of numbers. Underneath both is the ERP: understanding the data model, working with the ERP administrator and implementation partner on configuration and integration needs, and keeping AI and analytics initiatives grounded in the system of record. Reporting to the IT Director, this position is the operational leader of Fresh Origins’ AI and data initiatives and a core part of the company’s investment in AI-driven transformation. The role works closely with the EDI & Production Systems Coordinator, who manages EDI transactions, trading partner platforms, VIDA18 warehouse management, item data, and the commercial customer portal, and with stakeholders across Finance, Operations, Sales, and Production. It supports Fresh Origins’ mission of delivering the highest-quality microgreens and edible flowers through innovation and precision.

Requirements

  • Bachelor’s degree in Business Administration, Information Systems, Data Analytics, Industrial Engineering, or a related field, or equivalent experience.
  • 5+ years as a business analyst, systems analyst, or project manager in an ERP-driven environment (NetSuite, SAP, Dynamics, Oracle, or similar).
  • Proven record leading cross-functional projects end to end and managing vendors, consultants, or implementation partners.
  • Hands-on experience gathering requirements, mapping processes, and defining KPIs for operations, finance, or sales teams.
  • 1+ years leading or contributing to AI, machine learning, or intelligent automation initiatives in a business setting; experience rolling out enterprise generative AI tools is strongly preferred.
  • Experience working with a BI platform (Power BI preferred) and a data warehouse or data lake.
  • Working knowledge of ERP data structures and core transaction flows; NetSuite experience is a plus, not a requirement.
  • SQL for data validation and analysis; comfort with a cloud data warehouse (BigQuery or similar).
  • Power BI or equivalent BI tool; dashboard design and KPI definition.
  • Project management tools and methods (Agile or hybrid); requirements and process documentation.
  • Familiarity with generative AI platforms, AI-powered analytics, and automation tools; ability to evaluate vendors and pilot solutions.
  • Advanced Excel (pivot tables, Power Query, XLOOKUP); exposure to Python or scripting is a plus.
  • Business-first thinker: starts with the problem and the process, not the tool.
  • Strong project management discipline: scopes clearly, communicates status, manages risk, and finishes.
  • Clear communicator and teacher; explains AI to non-technical stakeholders, including executives and corporate, without hype.
  • Data-literate and analytical; comfortable questioning numbers and validating results.
  • Collaborative and pragmatic; builds trust across Accounting, Operations, and Sales.
  • Curious and self-directed, with a growth mindset toward AI and automation.
  • Organized and accountable; manages multiple vendors, projects, and deadlines at once.
  • Act as the trusted advisor to leadership on AI, analytics, and business systems.
  • Own outcomes, not just tasks: define success for each initiative, measure it, and report it.
  • Manage outside partners and consultants to deliverables, budget, and timeline.
  • Mentor the EDI & Production Systems Coordinator and other team members on analysis, data standards, and AI tools; potential future supervision of analyst-level staff.
  • Champion responsible AI adoption and data literacy across the organization.
  • Model professionalism, accountability, and continuous learning.
  • Prioritize the safety and well-being of co-workers by following all company safety protocols.

Nice To Haves

  • PMP, CBAP, or similar project or business analysis certification is a plus.
  • Experience in food production, agriculture, manufacturing, or distribution is a significant plus.

Responsibilities

  • Own the AI roadmap and project portfolio: prioritize initiatives by business value, feasibility, cost, and timeline; sequence them; and manage them end to end from discovery through adoption.
  • Educate leaders and key stakeholders on AI principles, capabilities, risks, and practical business applications; translate technical concepts into clear business recommendations.
  • Lead business analysis for AI use cases: interview stakeholders, map current processes, quantify manual effort and data breaks, and define requirements and success metrics before any tool is selected.
  • Run projects as the project manager of record: scope, timeline, resourcing, risk, testing, rollout, and status reporting for each AI and automation initiative.
  • Manage outside AI consultants and implementation partners day to day: set deliverables, review work, test outputs, and hold partners to scope, budget, and timeline.
  • Lead the AI-driven demand planning initiative from the business side: define the planning questions, coordinate data readiness (planting, harvest, yield, weather, holidays, sales), and validate model outputs with Production and Sales.
  • Support the rollout of AI-assisted order intake and customer service automation: process design, user acceptance testing, and clean handoff into ERP and customer-facing workflows in coordination with the EDI & Production Systems Coordinator.
  • Drive adoption of the company’s enterprise AI tools: identify use cases by department, deliver training and office hours, manage licenses, and track utilization and outcomes.
  • Pilot and evaluate AI capabilities for forecasting, anomaly detection, document processing, and workflow automation; recommend build, buy, or partner decisions.
  • Prepare AI program updates for company leadership and corporate stakeholders, including portfolio-level AI reporting and best-practice sharing.
  • Maintain the AI governance framework with the IT Director: responsible use, data privacy, vendor risk, and change management.
  • Own business continuity for AI tools, automations, and integrations once live: documentation, monitoring, fallback procedures, and clear ownership of what happens when a system fails.
  • Define and maintain KPI definitions with Finance, Operations, and Sales so leadership reports from a single source of truth.
  • Partner with the analytics team and outside partners on the company data lake and Power BI: prioritize dashboards, validate data, and drive adoption of governed reporting over manually built spreadsheets.
  • Analyze structured and unstructured data (transactions, customer service notes, emails, call records) to surface trends, exceptions, and opportunities that feed the AI roadmap and leadership decisions.
  • Identify where teams are manually assembling data the data lake already produces and migrate them to governed reporting.
  • Understand the ERP data model and core processes (order-to-cash, procure-to-pay, inventory, financial close) well enough to design AI and analytics solutions that fit how the business runs.
  • Translate business requirements into configuration and integration requests; work with the ERP administrator and implementation partner to deliver them.
  • Improve data connectivity across the business systems stack (NetSuite, Salesforce, Power BI, ADP, VIDA18, and EDI middleware) so AI and analytics initiatives run on connected, trusted data.
  • Champion master data quality across items, customers, vendors, and GL structure; lead cleanup and reclassification efforts that unblock reporting and AI.
  • Review ERP release notes and platform AI features; recommend adoption to leadership.
  • Document processes, data standards, and standard operating procedures for AI-supported workflows.

Benefits

  • Standard business hours with extended support during project go-lives and key business cycles.
  • Office environment with regular visits to greenhouse, production floor, cold storage, and warehouse areas to observe processes and work with users.
  • Routine use of computer, ERP and BI software, phone, and standard office equipment.
  • Occasional after-hours work for rollouts or vendor coordination.
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