Operations Manager, AI Enablement

Whip Around was born in 2016, originally to help freight companies in New Zealand tackle their paper-based compliance burden. It was while working for some of the globe’s largest freight companies that co-founder James saw first-hand how much time paper was costing fleet managers every day. Within a year the US market was calling loudly, and founders Tim and James were spending more time traversing the American market than anywhere else. Whip Around now has offices in Auckland, New Zealand, and Charlotte, North Carolina, servicing customers from coast to coast in the US and around the world. Team culture is at the heart of our success, with personal improvement being just as important as company outcomes. We boast a senior leadership team with experience from numerous successful global businesses, and we continue to double down on our vision to bring simplicity and efficiency to fleet management and compliance — increasingly powered by data and artificial intelligence. Reporting to the Director of Operations, the Operations Manager helps keep our AI tools and supporting systems running smoothly and efficiently. This role manages AI development and accuracy in our day-to-day systems, maintains integrations, and develops AI models that our teams depend on to continue growing the reliability and usage of AI in our business and to support our ability to scale. A key part of the role is supporting Whip Around’s AI enablement efforts. Under the direction of the Director of Operations, the Operations Manager will help identify practical opportunities for AI and automation, turn promising experiments into reliable, repeatable use cases, and embed those tools into everyday workflows to save time and improve consistency. We’re looking for someone who has hands-on experience getting AI use cases into real-world use and can show the value they delivered. Operational Delivery & Support

• Manage day-to-day operations within your area, supporting the Director of Operations to keep workflows, resources and projects on track and aligned to team goals.
• Track and report on operational KPIs against targets set with the Director, flagging performance gaps and helping put corrective action in place.
• Help manage operational budgets and tools, keeping an eye on spend and making sure we get good value from our systems and vendors.

AI Enablement & Use-Case Production

• Support the rollout and adoption of AI and automation tools across the team, providing the guides, training and hands-on help people need to use them confidently.
• Help identify and prioritize practical AI use cases tied to clear outcomes - reducing manual effort, improving consistency and saving time or cost.
• Take promising experiments through to reliable, repeatable use cases: gathering requirements, validating outputs, supporting rollout, and maintaining, updating and improving the tools once they’re live.
• Deliver early, practical “quick wins” in the first few months, then help establish simple routines for monitoring and improving the solutions in use.
• Keep live AI tools fed with accurate, current information so they stay reliable and trusted by the people using them.

Process Improvement & Systems

• Map and improve core operational processes, spotting bottlenecks where automation or AI could replace manual administration and sharing recommendations with the Director.
• Help maintain and improve core systems (e.g., Salesforce/HubSpot CRM, Jira), and flag integration gaps or usability issues in the tech stack.
• Document processes, tools and standard operating procedures so that knowledge is captured, repeatable and easy for the team to follow. Data, Reporting & Stakeholder Support
• Gather data needs from teams across the business and turn them into clear reports, dashboards and useful insights.
• Run regular audits of key business data to ensure accuracy, and work with teams to find and resolve sources of variance.
• Help prepare monthly and quarterly analytics for the Director and senior leadership, explaining findings clearly to both technical and non-technical audiences.

Collaboration & Team Support

• Work closely with the Director of Operations and partner with Sales, Customer Success, Finance and Product to keep work coordinated across teams.
• Bring structure, timelines and follow-through to operational projects so they stay on track.
• Mentor and support junior team members, and provide documentation, support and training for internal users.

Compliance & Quality

• Follow and help maintain responsible-use, data privacy and quality controls for AI and automation, so the tools we use stay safe and trustworthy.
• Support compliance with applicable data privacy regulations and partner with the Tech team on security where needed.
• Flag operational risks early, and perform other duties as assigned to support projects and departmental needs.

Bachelor’s degree in Business, Operations Management, Analytics or a related field (or equivalent practical experience).

• 5+ years of experience in software engineering, business systems, data engineering, business operations, or a related technical field, including experience delivering production automation or AI solutions.
• At least 1–2 years of hands-on experience designing, building, or deploying generative AI applications using LLMs, agent frameworks, or similar technologies.

Critical Competencies: Agentic Strategy & Delivery

• Partner with business stakeholders to identify, prioritize, prototype, and implement high-impact AI opportunities across the organization.
• Help define and execute the company's AI strategy and implementation roadmap.
• Lead AI transformation initiatives
• Drive adoption of AI solutions through training, documentation, and continuous improvement based on user feedback.

AI Engineering & Operations

• Experience deploying production AI applications • Prompt engineering and agent orchestration
• Designing evaluation frameworks and benchmarks for AI systems, including automated and human-in-the-loop testing
• Model evaluation and performance monitoring
• AI observability and quality assurance
• Managing hallucination risk and response accuracy
• Prompt optimization and, where appropriate, model fine-tuning, and guardrails and data quality and governance for AI systems: experience auditing, cleansing, and structuring source data from databases before it feeds into an LLM or agent
• Experience designing context-aware AI systems using retrieval, structured business data, memory, and tool access.
• Familiarity with data validation frameworks or QA checkpoints to catch bad or incomplete data before it reaches a production AI workflow
• Experience balancing model capability, latency, and cost for production AI applications.
• Evaluate emerging AI models, tools, and techniques, and recommending pragmatic adoption where they can provide measurable business value.

Enterprise Integration

• Strong working proficiency in Python, SQL (Microsoft SQL Server and/or PostgreSQL), and SOQL.
• Hands-on experience getting AI or automation use cases into real-world use, with examples of the value they delivered.
• Designing AI workflows that appropriately involve human review and approval for sensitive business processes.
• Experience integrating AI solutions into Salesforce using APIs, Flows, Apex, platform events, and standard automation tools while respecting Salesforce security and permission models.
• Experience integrating AI systems with enterprise applications, databases, APIs, and business workflows. • Experience with OpenAI, Anthropic, Google Gemini, or Azure AI services

Professional Skills

• Well organized and dependable, with the ability to manage multiple priorities and bring order to ambiguity.
• Strong analytical and problem-solving skills, with a genuine interest in finding patterns in data.
• Excellent interpersonal and written communication, with the ability to build strong, supportive working relationships.
• Able to communicate complex technical concepts clearly to both technical and nontechnical audiences. • High level of integrity, attention to detail and accuracy in work.
• Experience with process improvement and project coordination.
• A solid working understanding of data, metadata, and data auditing, cleansing, visualization and manipulation.
• Comfortable working in a fast-moving, growing environment with a bias toward practical, measurable results.

Preferred and Differentiated Competencies :

• Experience with enterprise security, governance, privacy, compliance and responsible AI practices.
• Experience with modern agent frameworks, orchestration platforms, or AI development SDKs is highly desirable.
• AWS, Azure, or GCP experience
• Nice to have: Docker and deployment workflows
• Git and software engineering best practices
• API design and integration
• Data engineering, ETL/ELT, API integrations, and workflow automation
• CRM data modeling and governance
• Knowledge of Salesforce Flows, Apex and Lightning Web Components
• Comfortable working with structured business data using SQL, spreadsheets, or BI tools.
• Experience with CRM and project tooling - Salesforce and/or HubSpot, and Jira/Confluence.
• Certifications such as Six Sigma, Lean, or an AI/automation credential are a plus.
• Previous experience in SaaS, Customer Success, or a technology environment
• Experience with vector databases or semantic search technologies.

Compensation : $130K - $160K USD, depending upon experience and location Unlimited PTO: Use your paid time off when you need it Subsidized Healthcare : A variety of subsidized medical plans to fit your needs Retirement Support: 401(k) matching to help you invest in your future. Family Friendly: Paid parental leave and caregiver support Growth & Development: Professional development plans and resources to support continuous learning. Following your application, a member of the Whip Around team will be in touch. If you have any accessibility requirements you can then let us know, so we can assist throughout the process. We participate in E-Verify and will verify employment eligibility via the I-9 Form. #J-18808-Ljbffr Whip Around