Head of Engineering

Old Mutual; Johannesburg; On-site; ZAR 1,500,000 - 3,000,000; Full time

Job summary

Old Mutual is seeking a Head of Engineering to lead software, data platforms and AI-enabled initiatives across the organisation. You will translate technology strategy into stable, secure and cost-conscious systems while embedding AI-assisted practices into the lifecycle.

You will build engineering capability, uphold governance, and drive measurable delivery outcomes through Chapter structures and cross-functional leadership.

Qualifications

• Bachelor's degree in computer science, Software Engineering or related field.
• 8+ years of technology or software engineering experience in complex delivery environments.
• At least 7 years of managerial experience, leading software teams.
• Experience leading cross-functional development teams and delivering complex projects.

Responsibilities

• Lead the engineering function across software, data, platform and AI domains.
• Define and execute an AI-enabled engineering strategy and roadmap.
• Build and scale internal developer platforms and governance.
• Ensure delivery speed, stability, security and regulatory compliance.

Skills

Agile Methodology

Artificial Intelligence Techniques

People Management

Software Engineering Competencies

Business Insight

Collaboration

Communication

Innovation

Customer Focus

Decision Quality

Education

Bachelor of Computer Science (BCoSc)

Tools

GitHub Copilot

Claude Code

Cursor

Azure

AWS

Google Cloud

Job description

Head of Engineering

Let's Write Africa's Story Together! Old Mutual is a firm believer in the African opportunity and our diverse talent reflects this. Job Description The Head of Engineering will be accountable for leading the development, modernisation and maintenance of applications, systems and platforms, and will be expected to translate the technology strategy into working systems that are stable, secure, resilient, cost-conscious and capable of supporting digital, data and AI-enabled business outcomes.

This is an AI-native leadership role: the successful individual will be expected to embed AI-assisted engineering practices into the software development lifecycle itself, in addition to delivering AI-enabled products and platforms for the business.

The Head of Engineering will be responsible for: Software and Product Engineering Platform, Infrastructure and DevOps Data Engineering and Analytics AI, Machine Learning and Automation Security Engineering Quality Engineering and Site Reliability Engineering

The role is particularly important where legacy platforms, complex integrations, regulatory expectations and increasing business demand create pressure on delivery and operational resilience and the successful individual must be able to improve delivery speed and quality while maintaining production stability, security and governance.

This is a leader of leaders role that sets standards, establishes delivery discipline, builds engineering capability, and holds teams accountable for measurable outcomes.

Key Result Areas: Quality Assurance Develop and maintain quality procedures and engineering standards; oversee testing, , certification of technology processes and quality controls for products and platforms. Project and Delivery Management Manage delivery of major engineering programmes and take personal accountability for a small number of business-critical projects. Digital Vision and Strategy Execution Collaborate on the digital roadmap and lead execution of workflows, processes and enablers that allow new applications, products and services to be delivered quickly while maintaining legacy applications and IT operations at optimal levels. Digital Talent Development Execute the strategy to grow engineering and digital talent through development plans, coaching, mentoring and improved employee experience. Data-Driven Product and Service Improvement Create the capability to proactively identify opportunities to improve digital products, services and user experiences over the long term.

Current and Target-State Analysis Document complex current-state and target-state processes and define the changes required to migrate to the target capability.

Leadership and Direction Translate function strategy into clear actions for teams; explain the link to organisational mission, vision and values; and motivate people to deliver local business goals.

Performance Management Set objectives for direct reports, manage performance, hold individuals accountable and take corrective action where required to achieve annual business objectives.

Information Security Define the business impact of security incidents and drive recommendations to prevent recurrence, in partnership with security and risk stakeholders.

Budgeting Manage departmental budget plans and ensure delivery and modernisation choices are cost-conscious and value-led.

Organisational Capability Building Assess capability gaps, prioritise development activity, implement formal development frameworks and strengthen the engineering talent pool.

Application Software Development Oversee complex existing and new applications by identifying areas for modification and improvement, and ensuring new applications meet customer and business requirements.

Application Software Roadmap Define and maintain the roadmap for complex application software development and prioritise engineering work in line with business needs.

Information and Business Advice Provide authoritative specialist advice to senior managers to support policy implementation, projects and change initiatives.

AI-Augmented Engineering and Developer Productivity Drive organisation-wide adoption of AI-assisted development tools (coding assistants, agents, automated testing and code review) across the software development lifecycle, and track their impact on delivery speed, quality and engineering capacity.

Platform Engineering and Internal Developer Platform Build and scale a self-service internal developer platform with golden paths, reusable components and automated guardrails, reducing cognitive load on engineering teams and accelerating time to production.

AI, Model and Data Governance Partner with risk, compliance and data stakeholders to embed responsible AI practices, model risk management and data governance controls into engineering delivery, ensuring AI and automation capabilities move from pilot to production safely and with appropriate oversight.

Engineering Metrics and Continuous Improvement Establish and report on delivery and reliability metrics (for example DORA metrics and SLOs/error budgets) to drive a culture of continuous improvement and evidence-based decision-making.

Chapter and Sub-Chapter Management The Head of Engineering will establish and lead a Chapter operating model, grouping engineers by discipline (including Software Engineering, Data Engineering, Platform and DevOps, Quality Engineering and SRE, Security Engineering, and AI/ML) across product squads and delivery teams. Each Chapter will be led by a Chapter Lead accountable for technical standards, hiring quality, career progression and skills development within their discipline, working alongside Squad and Product Leads who direct day-to-day delivery priorities. The Head of Engineering is accountable for the overall health and capability of the Chapter structure, including maintaining competency frameworks and career ladders for each discipline, identifying and closing skills gaps through targeted hiring, upskilling or redeployment, and monitoring chapter-level health indicators such as engagement, attrition, internal mobility and time-to-competency for new joiners.

In an AI-native engineering organisation, each Chapter Lead will also be accountable for driving the adoption of AI-assisted tools and practices within their discipline and for measuring the resulting impact on delivery speed, quality and engineering capacity, ensuring that technical excellence and AI-augmented ways of working are embedded consistently across the engineering function rather than left to vary by team.

Qualifications, Skills, Experience Required

• Bachelor's degree in computer science, Software Engineering or a related field.
• At least 8 years of general technology or software engineering experience, with significant exposure to complex delivery environments.
• At least 7 years of managerial experience, including leadership or mentorship of software engineering teams.
• Experience leading cross-functional development teams and delivering complex, business-critical projects.
• Strong understanding of software development across front-end, back-end, integration and platform technologies.
• Experience defining and maintaining application software roadmaps aligned to business priorities.
• Proven ability to balance delivery speed, production stability, security, risk and quality.
• Excellent problem-solving, debugging, communication, collaboration and leadership skills.
• Commitment to staying current with emerging technology trends, including cloud, microservices, automation, data, AI and AIagentic engineering tools.
• Demonstrated experience leading AI-augmented software engineering organisations, including adoption of AI coding assistants and agentic development tools at scale.
• Working knowledge of platform engineering, internal developer platforms and metrics-driven engineering culture.

Preferred

• Experience with cloud services such as Azure, AWS or Google Cloud.
• Experience with microservices architecture and modern integration patterns.
• Agile or Scrum certification and familiarity with project management and delivery tooling.
• Experience modernising mission-critical legacy systems.
• Experience moving AI, GenAI or automation capabilities from pilot to production with appropriate governance.
• Experience operating in a regulated or high-control environment where audit, resilience and evidence matter.
• Hands-on familiarity with AI coding assistants and agentic tools (e.g. GitHub Copilot, Claude Code, Cursor) and their governance in an enterprise setting.
• Exposure to LLMOps/MLOps practices and modern data architectures such as data mesh or lakehouse.
• Experience with cloud FinOps and cost optimisation for engineering and AI workloads.
• Awareness of emerging AI regulation and data protection requirements (e.g. POPIA, GDPR, EU AI Act) relevant to a regulated financial services environment.

Skills

• Agile Methodology
• Artificial Intelligence Techniques
• People Management
• Software Engineering Competencies
• Business Insight
• Collaborates
• Communicates Effectively
• Cultivates Innovation
• Customer Focus
• Decision Quality
• Develops Talent
• Drives Engagement
• Education Bachelor of Computer Science (BCoSc) (Required)

Closing Date

30 September 2026 , 23:59

The Old Mutual Story

The Old Mutual Story! Old Mutual is a premium African financial services organisation that offers a broad spectrum of financial solutions to retail and corporate customers across key market segments in 14 countries. The lines of business include Life and Savings, Property and Casualty, Asset Management and Banking and Lending. We are rooted in our purpose of Championing Mutually Positive Futures Every Day and believe that a great customer experience is anchored in a great employee experience.