1.Purpose of the Role

The CTO is accountable for how #Monvia builds, scales, and operates its software platform. This role owns the engineering execution system: platform integrity, architecture, delivery quality, security, reliability, developer effectiveness, and design system coherence - ensuring Monvia can scale product capability without degrading quality or confidence.

A core part of this role is to drive AI and agentic AI adoption across the business (in partnership with peers), ensuring adoption is safe, measurable, compliant, and value-creating for regulated enterprise insurer environments.

2. Scope & Key Accountabilities

2.1 Engineering & Platform Excellence

• Lead Product Engineering (core platform squads) to deliver scalable, maintainable capability.
• Own Architecture: target architecture, domain boundaries, integration patterns, and extensibility model.
• Own Platform Engineering: CI/CD, environments, tooling, and developer experience (DevEx).
• Own Reliability/SRE: SLO framework, observability, incident practices, and operational readiness.
• Own Security Engineering/AppSec: secure SDLC, vulnerability management, and control automation.
• Own the Quality System via QA leadership: standards, automation frameworks, and non-functional quality.
• Own Design as a platform function: design system, UX coherence, and usability quality across modules.

2.2 AI & Agentic AI Adoption (Explicit Accountability)

• Define AI/agentic engineering standards, guardrails, and approved toolchain (security, privacy, auditability).
• Embed AI across the SDLC: coding assistance, reviews, refactoring, test generation, documentation, and knowledge management.
• Enable agentic workflows where appropriate (e.g., test orchestration, release evidence collation, incident triage) with bounded scope and human override.
• Partner with Head of Product & Labs to industrialise successful AI prototypes into core platform capabilities.
• Ensure AI adoption aligns with enterprise insurer expectations and Monvia’s AI Adoption Charter, including data handling and client constraints.

2.3 Technical Strategy & Architecture

• Maintain a clear platform evolution roadmap balancing innovation, maintainability, and operational risk.
• Manage technical debt deliberately with transparent trade-offs and measurable outcomes.
• Ensure configuration and integration approaches remain coherent, scalable, and reusable across clients.

2.4 Delivery System & Ways of Working

• Operate an engineering management system that improves flow: lead time, deployment frequency, change failure rate, and Mean Time to Resolution (MTTR).
• Set engineering standards and practices that improve quality and predictability without excessive bureaucracy.
• Establish clear interface rules so Delivery (Projects) can execute within guardrails without polluting the core platform.

2.5 Leadership & Capability

• Build and mentor engineering leaders (Engineering Leads, Tech Leads, Architects).
• Own engineering hiring strategy, capability uplift, performance, and succession planning.
• Create a culture of clarity, accountability, continuous improvement, and calm execution.
• Be the technology advisor to the CEO (and Leadership)
• Demonstrate thought leadership and position Monvia in the market through strong client and market engagement (events

3. Explicitly Out of Scope (By Design)

• Product strategy, roadmap prioritisation, or portfolio trade-offs (owned by Head of Product & Labs, with CEO arbitration).
• Client project delivery commitments, sequencing, or project governance (owned by Chief Delivery Officer (CDO)).
• BAU/Run service ownership and operational commitments (owned by CIO / Head of Managed Services).
• Commercial negotiation and sales commitments.

4. Key Relationships

• CEO - strategic trade-offs, investment alignment, escalation when priorities collide. Technology advisor to the CEO
• Head of Product & Labs - translate product intent into scalable capability; Labs → Core promotion pipeline.
• Chief Delivery Officer (CDO) - enable delivery within guardrails, patterns and tooling alignment.
• CIO / Head of Managed Services - operational readiness, incident learning, run feedback loops.
• Security / Risk stakeholders (internal and client) - assurance and evidence. 

5. Measures of Success

• Platform scales without degradation in reliability, security, or delivery velocity.
• Engineering ships predictably and safely (improved flow metrics and release confidence).
• Quality is embedded (lower defect escape rate, stronger automation coverage, improved NFR performance).
• Delivery executes effectively without compromising core integrity (clear constraints, reduced bespoke rework).
• AI adoption is measurable and safe (productivity uplift, improved quality, improved MTTR, governance compliance).

6. Leadership Style

• Brings clarity, not control; sets guardrails, not gates.
• Calm under pressure; values disciplined execution and learning.
• Balances pragmatism with long-term platform thinking.
• Earns trust through technical credibility and authentic leadership.
• Builds a culture that embraces AI safely and productively.