ScaleEnabler is Hiring

SCALEENABLER LEADERSHIP ROLE

Chief Operating Officer

ScaleEnabler is building an AI-enabled professional-services business designed around repeatable methodologies, reusable intellectual property and increasingly sophisticated AI agent systems.

We are looking for a Chief Operating Officer who can work closely with the founder to turn that capability into a disciplined, scalable operating business.

The mandate

The COO will help build the operating system of ScaleEnabler as the business moves from founder-led innovation and prototyping towards repeatable commercial delivery. The role connects strategy, commercial execution, client delivery, operational discipline, quality, people, capacity, process, measurement and scalability.

What you will own

• Designing and implementing ScaleEnabler’s scalable operating model.
• Turning methodologies, intellectual property and successful prototypes into repeatable delivery processes.
• Establishing delivery disciplines, standards, controls and operating rhythms.
• Building implementation capability as client volume increases.
• Translating strategy into executable plans, priorities and accountabilities.
• Establishing useful operational and commercial measures, capacity planning and resource allocation.
• Strengthening project management, client onboarding, delivery, quality assurance and ongoing support.
• Developing the operating infrastructure required for partnerships and larger client engagements.
• Determining what should remain founder-led and what should become institutional capability.
• Working closely with the CTO so technical capability and delivery capability scale together.
• Helping recruit, structure and develop the wider team while protecting quality as throughput increases.

What success looks like

• ScaleEnabler can take on substantially more work without delivery depending on heroic founder effort.
• Engagements follow repeatable but adaptable delivery disciplines.
• Responsibilities and decision rights become clearer.
• Delivery quality is measurable and consistent.
• Methodologies and intellectual property increasingly become institutional assets rather than founder-held knowledge.
• Operational bottlenecks are identified early, without unnecessary bureaucracy.

Who we’re looking for

Someone who has helped build or scale a consulting, professional-services, technology or similarly knowledge-intensive business; combines strategic thinking with operational execution; and is comfortable building systems where little infrastructure currently exists.

You will understand project and service-delivery economics, introduce discipline without suffocating entrepreneurship, be commercially minded and be comfortable working directly with a founder. You will communicate clearly, make ambiguity manageable, care about execution and measurable outcomes, and be excited by the implications of AI for professional services.

The opportunity

This is an opportunity to help shape the operating model of ScaleEnabler while it is still being formed, rather than inherit a mature corporate operating structure. The work is to turn a credible direction into a business that can deliver with increasing repeatability and quality.

SCALEENABLER LEADERSHIP ROLE

Chief Technology Officer

ScaleEnabler is moving from sophisticated AI prototypes towards production-engineered AI systems.

The technical challenge is increasingly not simply whether an AI agent can perform an intelligent task. It is whether complex, stateful, evidence-dependent agent systems can perform reliably, securely, observably and repeatedly in production. We are looking for a Chief Technology Officer who wants to help solve that problem.

The mandate

The CTO will work closely with the founder to establish ScaleEnabler’s production AI engineering capability and technical direction. The role bridges AI architecture, software engineering, agent engineering, production reliability, security, governance, evaluation, observability, data, integration, reusable components and technical strategy.

What you will own

• Defining ScaleEnabler’s production AI architecture and turning successful prototypes into robust production systems.
• Establishing the technical foundations of the ScaleEnabler Agent Factory.
• Designing reusable agent architectures, components and engineering patterns.
• Determining appropriate boundaries between LLM intelligence and deterministic software.
• Creating explicit workflow and state management for complex agent systems.
• Establishing evidence persistence, provenance and traceability.
• Building evaluation, regression testing, quality measurement, observability, tracing and production diagnostics.
• Designing failure handling, recovery, resilience, security, privacy, access controls and responsible AI engineering.
• Setting technical governance and production-readiness standards for tools, integrations, data and external systems.
• Making pragmatic build-versus-buy and platform decisions, while avoiding unnecessary vendor lock-in where commercially sensible.
• Managing engineering economics, including reliability, maintainability and operating cost.
• Working with the COO so engineering and delivery capability develop together, and helping recruit and develop future technical capability.

The Agent Factory

ScaleEnabler research has identified 294 potential specialised advisory agents across 13 advisory disciplines. Twenty-six were explicitly identified as substantial or complex systems. The emerging hypothesis is that many of these may reduce to roughly 25–35 reusable agent archetypes, with specialised configurations, knowledge, tools and outputs layered on top.

The CTO would help determine how that high-level hypothesis becomes production engineering, without exposing the proprietary implementation details that make the capability distinctive.

What success looks like

• Complex agents become increasingly repeatable to engineer.
• Prototypes can move into production through a defined engineering pathway.
• State and evidence are explicit rather than fragile or implicit.
• Deterministic calculations and controls sit in software where appropriate.
• AI quality can be evaluated rather than merely observed anecdotally.
• Failures are traceable and recoverable.
• Security and governance are designed in rather than added later.
• Reusable architecture reduces the cost and time of subsequent agent development.
• ScaleEnabler develops genuine internal production-engineering capability.

Who we’re looking for

Someone with substantial software, platform or AI engineering depth who has taken AI or complex software systems beyond the prototype stage. You understand modern LLM and agent architectures, and that production AI requires more than prompting.

You think naturally about state, evaluation, observability, security, reliability and failure modes; make pragmatic build-versus-buy decisions; and remain technically hands-on where necessary. You can communicate architecture clearly to non-technical executives and clients, enjoy building foundations rather than inheriting them, work closely with a founder while challenging assumptions constructively, and want to build reusable engineering capability rather than one-off demonstrations.

The opportunity

This is an unusual opportunity to influence the technical architecture while ScaleEnabler’s production approach and Agent Factory are still being formed. The work is demanding by design: establish the foundations that let ambitious agent systems become credible production capability.