AI & Automation Manager - 21327

Evaluate workflows throughout the portfolio and identify high-impact opportunities for AI and automation.

Review processes involving:

• Sales

• Customer service

• Operations

• Finance

• Administration

• Marketing

• Reporting

• Lead management

• Internal communication

• Data processing

• Executive operations

Prioritize initiatives according to business impact, implementation complexity, cost savings, time savings, and scalability.

Map existing processes before automating them.

Understand:

• Who performs each task

• What information is required

• Which systems are involved

• Where bottlenecks occur

• Which decisions require human judgment

• Which activities can be automated

• Where AI can augment employees rather than simply replace manual steps

Redesign workflows before implementing technology so inefficient processes are not merely automated in their existing form.

Build and deploy integrations between business systems.

This may include:

• Automated data movement

• CRM workflows

• Lead routing

• Automated reporting

• Notifications and alerts

• AI-generated summaries

• Task creation

• Communication workflows

• Document processing

• Customer follow-up sequences

• Executive reporting

• Operational dashboards

Identify appropriate use cases for generative AI and other AI technologies.

Potential use cases could include:

• Communication summarization

• Customer support assistance

• Lead qualification

• Internal knowledge retrieval

• Document analysis

• Automated reporting

• Research

• Sales support

• Marketing workflows

• Executive briefings

• Process documentation

• Decision-support tools

Because this role supports multiple businesses, the AI & Automation Manager will need to understand different operating environments quickly.

A workflow that makes sense for a 100+ employee home care company may differ substantially from one required by a payment processor, roofing company, real estate operation, or reputation management business.

The successful candidate must be able to adapt solutions to different business models rather than applying the same technology indiscriminately.

Before implementing major automation projects, determine the expected value.

Consider:

• Hours saved

• Labor cost reduction

• Revenue impact

• Error reduction

• Customer experience improvement

• Faster turnaround

• Better management visibility

• Scalability

The founder wants someone with enough business acumen to understand why an automation matters—not merely whether it can technically be built.

Help employees and company leaders adopt new AI-enabled processes.

Document workflows, create appropriate training resources, and ensure new tools are actually used.

Monitor adoption and refine systems based on real-world feedback.

Regularly review implemented systems to determine whether they are delivering the intended results.

Identify new technologies and AI capabilities that could provide meaningful business value.

The expectation is continuous experimentation and improvement rather than one-time implementation.

The ideal candidate sits at the intersection of:

A technically excellent candidate who cannot understand business processes will not be sufficient.

Likewise, a business operator who understands AI conceptually but cannot implement practical solutions will not be sufficient.

We need someone capable of understanding a business problem, designing the solution, and getting that solution operational.

• Demonstrated experience implementing AI and automation within real businesses

• Strong knowledge of modern generative AI tools and platforms

• Experience integrating business applications and workflows

• Strong process-mapping and workflow-design capability

• Understanding of APIs, integrations, and automation architecture

• Ability to evaluate emerging AI technologies

• Strong business and operational acumen

• Experience working across multiple departments or business functions

• Excellent English communication

• Ability to communicate technical concepts to non-technical stakeholders

• Strong project management and implementation skills

Business-first thinking: Technology exists to improve the business—not the other way around.

Automation mindset: You instinctively recognize repetitive processes that should not remain manual.

Technical curiosity: You continuously explore new AI capabilities and tools.

Execution: You can take an idea from concept through implementation.

Resourcefulness: You can solve unfamiliar technical and operational challenges.

Cross-functional communication: You can work with executives, operators, and employees.

ROI orientation: You understand the financial and operational impact of what you build.

Ownership: You are responsible for whether solutions actually work—not simply whether they were technically deployed.

The AI & Automation Manager will progressively create measurable improvements throughout the portfolio.

Success may include:

• Significant reductions in manual administrative work

• Faster internal workflows

• Improved customer response times

• Automated reporting

• Better executive visibility

• Improved lead management

• Reduced repetitive employee tasks

• More effective use of company data

• Increased productivity without proportional headcount growth

• Consistent AI adoption across the portfolio

Ultimately, this individual should become the portfolio's internal expert on how AI can materially improve the way each business operates.