The Opportunity

What You Will Own

1. Technology Execution & Delivery

• Run Technology on clear weekly priorities with an owner, deadline and measurable outcome for every major initiative.
• Establish strong engineering execution across product development, integrations, automation, infrastructure and AI.
• Track commitments through completion — not merely development activity.
• Identify blockers early and make fast build/buy/outsource decisions.
• Hold internal teams and external partners accountable for scope, timelines, quality and business outcomes.
• Build clear visibility from:

• Develop engineers and technology managers into stronger owners and future leaders.
• Create sufficient documentation, architecture standards and ownership so no critical system depends on one employee or vendor.

Success means:

2. Business-First Technology Strategy

• Deeply understand how Ergode makes money across marketplaces, brands and channels.
• Understand marketplace fees, margins, inventory, pricing, advertising, catalogue operations, fulfilment and customer experience.
• Own the Technology & AI roadmap based on impact on:
  • Revenue
  • Gross margin
  • Productivity
  • Operating cost
  • Speed
  • Customer/vendor experience
• Work directly with business heads to identify operational bottlenecks.
• Challenge processes that should be eliminated or simplified before automating them.
• Translate business problems into scalable technology solutions.
• Own technology economics including cloud, AI/token usage, software licences, development and outsourcing.
• Report technology performance to leadership in business outcomes rather than project activity.

3. AI, Agents & Intelligent Automation

• Identify high-volume and high-value manual work suitable for AI or automation.
• Build and deploy AI agents and GenAI workflows into real production environments.
• Develop reusable AI architecture rather than disconnected experiments.
• Integrate AI into areas including:
  • Catalogue and content
  • Marketplace listings
  • Pricing
  • Inventory
  • Customer support
  • Sales
  • Finance
  • HR
  • Reporting and decision support
• Build with LLM APIs, RAG, agentic workflows, orchestration frameworks and workflow automation.
• Establish before/after baselines for every major automation.
• Measure:
  • hours/FTE capacity saved
  • cycle-time reduction
  • cost reduction
  • quality improvement
  • revenue/margin impact
  • user adoption
• Kill pilots that do not produce value and scale the ones that do.
• Ensure business teams actually adopt what Technology builds.

We are not looking for:

We are looking for:

4. E-commerce Platforms & Marketplace Technology

• Marketplace integrations including Amazon SP-API, Walmart, eBay and other channels.
• Catalogue and listing infrastructure.
• Pricing and quantity synchronization.
• Order processing.
• Inventory and warehouse integrations.
• Returns, refunds and reconciliation workflows.
• Marketplace reporting and operational intelligence.
• API reliability and monitoring.

5. Product & Platform Ownership

• evaluating existing architecture,
• identifying technical debt,
• establishing clear module ownership,
• improving reliability and usability,
• prioritising development based on business value,
• and driving adoption after launch.

6. Data Foundation & Decision Intelligence

• Build reliable data flows across business systems.
• Establish clear sources of truth for critical business information.
• Reduce duplicate datasets and manual reconciliation.
• Improve data quality and ownership.
• Enable dashboards and AI systems to consume trustworthy business data.
• Build APIs and integration layers that allow new agents and applications to be deployed quickly.

7. Architecture, Cloud & Engineering Quality

• Review architecture for scalability, reliability, maintainability, security and cost.
• Establish coding, testing, documentation and deployment standards.
• Strengthen CI/CD and monitoring.
• Review estimates rather than blindly accepting them.
• Prototype when speed requires it.
• Make pragmatic technology choices rather than over-engineering.

8. Security, Reliability & AI Governance

• Cloud and infrastructure reliability
• Monitoring and uptime
• Incident management
• Root-cause analysis
• Backups and disaster recovery
• Identity and access management
• SSO
• Endpoint/device security
• Data protection

• which company information can be shared with which AI systems,
• permissions available to AI agents,
• human review requirements for critical decisions,
• auditability,
• and acceptable AI use.

9. Build vs Buy vs Outsource

• requirements,

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  architecture,
• vendor selection,
• commercial evaluation,
• milestones,
• SLAs,
• quality,
• security,
• source code,
• documentation,
• handover.

What Success Looks Like

Execution

• Major technology initiatives have clear owners, deadlines and outcomes.
• Delivery predictability improves materially.
• Chronic technology bottlenecks reduce.

AI & Automation

• Multiple AI agents/workflows are operating in production.
• Automation impact is quantified monthly.
• Manual workload is measurably reduced in targeted processes.
• Business adoption is visible rather than assumed.

Core Platforms

• Critical marketplace and internal systems become more reliable.
• Technical ownership and documentation improve.
• Important business workflows no longer depend on fragile manual processes.

Data

• Critical catalogue, inventory, order and operational data become more connected and trustworthy.

Business Partnership

• Business leaders increasingly bring problems to Technology because they expect working solutions, not project discussions.

Who We Are Looking For

Must-Haves

• 10+ years of meaningful technology experience.
• 5+ years leading engineering/technology teams.
• Evidence of personally owning major technology delivery.
• Strong understanding of software engineering, architecture, APIs and integrations.
• AI/automation systems deployed into production with measurable impact.
• Practical experience with:
  • LLM APIs
  • RAG
  • AI agents / agentic workflows
  • Python
  • workflow automation platforms such as n8n/Make or equivalent
• Cloud experience across AWS, Azure or GCP.
• API/integration architecture experience.
• DevOps, deployment and monitoring understanding.
• Ability to evaluate architecture, code/design decisions and engineering estimates.
• Experience managing external technology partners.
• Experience owning meaningful technology budgets.
• Strong business and commercial orientation.

Strongly Preferred

• E-commerce
• Marketplaces
• Retail technology
• D2C
• SaaS/platform businesses
• ERP/OMS/WMS
• Amazon SP-API or other marketplace integrations
• High-volume order/catalogue/inventory systems
• AI-first enterprise transformation

Who Will NOT Fit This Role

• Your experience is predominantly IT infrastructure/helpdesk.
• Your leadership style is primarily delegation without technical depth.
• Your AI experience consists mainly of courses, certifications or prototypes.
• You measure success by projects delivered rather than business outcomes achieved.
• You require large teams before you can execute.
• You prefer lengthy planning cycles over shipping, learning and improving.
• You cannot challenge engineers, vendors and business leaders when necessary.

The Person Behind the Resume