Group Architect

Technical Direction and Design

Software architecture (primary focus)

• Owns domain boundaries and the decomposition of large service estates, and consolidates concepts that have been built more than once.
• Owns the standards for API and event contracts, including versioning, deprecation and schema ownership.
• Owns the data position: which system owns what, how it is reached across boundaries, and how personal information is protected.
• Owns the sanctioned technology set and its lifecycle, agreed with the Heads of Technology.
• Decides where business rules and process orchestration belong, and stops competing engines accumulating.
• Sets the approach for correctness-critical systems, for designing at scale, for building many products on shared foundations, and for isolating third-party failure.

Cloud and platform architecture

• Owns the target platform architecture and the identity, secrets, observability and resilience standards the central cloud team delivers against.
• Owns the group cloud position: where the estates converge, and where they stay different.

Delivery and Execution

• Builds reference implementations and proofs of concept, in application code as well as infrastructure.
• Reviews application and infrastructure changes with technical authority, including sitting with a team to refactor a boundary.
• Sets and approves the standards the group's application templates must meet. The development function builds the templates.
• Works in the group's delivery model, where AI assistants produce much of the code and humans are accountable for review.

Governance, Risk and Compliance

• Keeps the group-mandatory standard set deliberately small (Section 5) and justifies anything added to it.
• Owns the quality model: automated scanning is the hard gate, AI-assisted review is a quality pass, and AI is never the sole approval.
• Designs to POPIA, PCI-DSS and ISO 27001 obligations, with controls built into templates and the platform rather than relying on discipline.
• Treats cost as a design input and tests expensive choices against doing nothing.

Stakeholder and Business Partnering

• Convenes the group architecture forum with the Heads of Technology and business technology leads, where group standards are agreed rather than announced.
• Works with Heads of Technology as peers, winning adoption on merit and respecting that business units differ in domain, regulation and history.
• Presents architecture to leadership with options, cost, risk and a recommendation.
• Partners with Information Security, which supports the architecture function without owning delivery.

Continuous Improvement and Innovation

• Treats friction in the developer experience as an architectural defect, and acts on builder feedback.
• Drives down duplicated capability and technology version spread.
• Raises architectural capability across the engineering group.
• Evaluates new technology against what the group can realistically operate.

People Leadership

Not applicable: individual contributor role. (Cluster removed per template instruction.)

• A relevant tertiary qualification is advantageous
• Architecture certifications such as TOGAF are neither required nor a differentiator.

Essential

1. 10 or more years in software engineering, including substantial hands-on development.
2. At least 2 years operating at architecture level, whatever the job title said. Staff and principal engineers who have owned architecture for a multi-team estate qualify. What matters is the evidence: has led a domain decomposition on a live system, and has set standards that teams outside their reporting line actually adopted.
3. Deep distributed systems and application architecture: domain decomposition, service boundaries, API and event contract design, and data ownership.
4. Event-driven architecture at estate scale, with experience of more than one paradigm. The group runs several in parallel and they need reconciling.
5. Production depth in .NET, Java or Go, enough to review service code credibly and refactor a boundary alongside a team.
6. Cloud architecture depth, including identity, secrets and least-privilege design, with enough multi-cloud literacy to form a group position.
7. Currently hands-on in application code and infrastructure.
8. Has modernised a legacy estate in practice, not only planned one, and can say what went wrong.
9. Builds agreement across teams that do not report to them.

Advantageous

Domain-driven design on a large estate · more than one of .NET, Java and Go · breadth across correctness-critical, high-scale consumer and process-driven systems · Kubernetes and managed container platforms at design level · OpenTelemetry and observability strategy · PCI-DSS, POPIA or ISO 27001 experience · South African market context · public writing, talks or open source.

SKILLS AND CAPABILITIES

1. Domain decomposition that produces boundaries teams can actually work to.
2. Contract design for APIs and events, with a clear position on versioning, delivery semantics, ordering and replay.
3. Correctness-critical design where being wrong costs money or breaches a regulation: idempotency, reconciliation, auditability.
4. Designing for scale and integration load: read paths, caching, edge delivery, and isolating third-party failure.
5. Data architecture and ownership, including protecting personal information by design.
6. Hands-on technical authority across application code and infrastructure, credible enough that engineers accept the review.
7. Designing for AI-assisted delivery, and reliably spotting generated output that is plausible but wrong.
8. Winning agreement without authority, and explaining trade-offs to leadership clearly.

 DIGITAL AND AI FLUENCY

At Ignition Group, digital and AI fluency is not a nice-to-have — it is a core performance requirement for every role, at every level. As AI and automation reshape how work gets done, the ability to work confidently and responsibly alongside these tools is as fundamental as any technical or professional skill.

What this means in practice:

• Digital fluency — navigating and using digital platforms, tools, and systems relevant to your role with confidence and competence
• AI tool adoption — actively using approved AI productivity tools (e.g., Microsoft Copilot) to improve the quality, accuracy, and efficiency of your work
• Data literacy — reading, interpreting, and applying data and AI-generated outputs to make better decisions, not replacing your judgement but sharpening it
• Automation awareness — recognising tasks and processes that can be improved through automation, and contributing to those improvements
• Learning agility — staying curious, upskilling continuously, and adapting as tools and practices evolve
• Responsible and ethical AI use — understanding data privacy obligations, the limits of AI-generated content, and applying sound human judgement at all times