AI Operations Lead

What is the role?

As the Collingwood AI Operations Lead, you are responsible for maintaining and optimising the “Collingwood Operating System.” Your mandate is to support our internal functions—client delivery, capacity planning, knowledge management, and finance—by building and managing the technical tools that power them. You will work with leadership to define the “what,” and your focus will be on the “how”—delivering efficiency, stability, and data integrity. Your primary mandate is to turn the business’s AI strategy (as defined by the leadership team) into functioning, production-ready tools for the advisory team.

Role responsibilities

1. Implementing AI strategy and infrastructure

• You will implement the business’s AI strategy as defined by leadership.
• You will build the vehicle. You are responsible for taking defined strategic goals—such as “automate capacity planning”—and configuring the technology to achieve them.
• You will research and recommend tools to support the roadmap, providing technical input to help leadership make build-vs-buy decisions.
• You will scope projects, set realistic timelines and KPIs (e.g., time saved on due diligence, accuracy of risk models), and manage budget.
• You will demonstrate the commercial impact and ROI of your initiatives.

2. Tech stack management and integration

You will maintain the holistic view of our technology ecosystem.

• Audit and fix: Regularly check the ecosystem (CRM, capacity planning, project management) to identify data silos and fix inefficiencies.
• Build connections: Execute the roadmap to connect these systems, ensuring data flows correctly across the business.
• Configure: Set up standard SaaS tools and build necessary integrations (via middleware/APIs) to ensure smooth operations.

3. Operationalising AI and automation

You will bridge the gap between tools and daily tasks.

• Build workflows: Configure AI agents and automation workflows for our advisory and operations teams.
• Execution: Manage the technical side of deployment, from testing tools to rolling them out to users.
• Security first: Ensure all configurations adhere to agreed data governance and security standards to protect IP.

4. Adviser and delivery enablement

Our advisory team is the engine of our delivery. You will build and maintain the systems that allow them to work seamlessly.

• Digitise processes: Turn our proprietary ways of working into digital checklists and workflows that guide execution.
• Reduce friction: Continually tweak systems and workflows to remove administrative blockers and improve user experience.

5. Support and adoption

Deployment is just the start. You are responsible for helping the team move to the new way of working.

• Support adoption: Create documentation, record training videos, and run training sessions to help the team use new tools.
• Monitor usage: Track utilisation rates to see who is using the tools and offer help where adoption lags.
• Feedback loop: Gather user feedback to make the new tech the path of least resistance.

6. R&D and experimentation

You will keep the business up to date with new capabilities.

• Run the sandbox: You will have allocated time to test specific tools and features as requested or identified.
• Test and report: Pilot new models and automation tools in a safe environment and report back on their viability to leadership.
• Efficiency focus: Identify time-saving opportunities in daily workflows and propose technical solutions.

About you

We are looking for a Technical Operations Manager—someone who loves building processes and connecting systems.

Essential experience and capabilities:

1. Technical skills and automation

• Integration proficiency: You have strong skills in connecting business systems (CRM, PM tools, Finance). Proficiency with integration platforms like Make (formerly Integromat), n8n, or Zapier is essential.
• Scripting for troubleshooting: You are comfortable reading and modifying Python or JavaScript to troubleshoot API payloads or customise workflows.
• Structured data: You have a strong ability to organise data for AI processing. You know how to turn a messy folder of PDFs into a structured data source.
• Stack familiarity: Hands-on experience administering standard consultancy SaaS tools (e.g., HubSpot, Xero, Notion, Float).

2. Support and training

• Process improvement: You can point to examples where you helped a team move from a manual process to a digital one.
• Documentation: You create clear, helpful training materials (videos, guides) that make it easy for non-technical staff to use your tools.
• Remote support: Experience supporting a remote or freelance workforce, understanding how to build tools that are intuitive enough to require minimal support.

3. Operational mindset

• Practicality: You focus on what works. You prefer simple, robust solutions over complex, “cool” tech that breaks easily.
• Structured testing: You can run a small test (“Let’s try this tool for one week”) and clearly report on whether it worked or not.
• Vendor management: You are comfortable acting as the primary technical point of contact for existing vendors and ensuring we are getting value from our subscriptions.
• Organised delivery: You use project management basics (Kanban/Task lists) to keep track of your work and communicate progress clearly.

Desirable

• Professional services experience: Experience working inside a consultancy or agency environment.
• Compliance basics: Awareness of GDPR and data privacy principles.

What success looks like in 12 months:

• Migration success: Key manual workflows have been successfully moved to automated alternatives and are being used daily.
• Sandbox value: You have tested and reported on multiple potential tools, saving the company from bad investments.
• Stable systems: The “Collingwood Operating System” is running smoothly with minimal downtime or data errors
• Commercial impact: You have been able to demonstrate the commercial impact and ROI of your initiatives