1508 Full Stack Developer (Expert)

Imizizi; Gauteng; On-site; ZAR 1,000,000 - 1,800,000; Full time

Job summary

Imizizi seeks an experienced software engineer to design, build, test, deploy and operate secure, scalable data products and platform capabilities in a DVF context.

You will own technical delivery from discovery through production, develop Python and Java components, and build AI-enabled solutions with reusable accelerators, while collaborating with cross-functional teams to ensure reliability and governance.

Qualifications

• Seven+ years of experience delivering complex production software.
• Expert-level delivery with Python and/or Java.
• Experience with data engineering and integration.
• AI-assisted or AI-native engineering experience.
• Advantageous certifications in AWS, Java, Python, Kubernetes, Terraform or AI.

Responsibilities

• Design, build, test, deploy and operate secure, scalable DVF software and data products.
• Own technical delivery from discovery to production and support.
• Develop Python and Java components for data processing and APIs.
• Build AI-enabled solutions, including agents, RAG patterns and guardrails.
• Run automated tests and build CI/CD pipelines and IaC.
• Collaborate with stakeholders to deliver measurable outcomes.

Skills

Python

Java

Data engineering

Architecture

DevOps

Agile

AI governance

Education

Bachelor's degree in Computer Science or related field

Tools

AWS

Kubernetes

Terraform

Job description

ROLE & RESPONSIBILITIES:

• Design, build, test, deploy and operate secure, scalable and maintainable DVF software, data products and platform capabilities.
• Own technical delivery from discovery and design through implementation, release, monitoring, support and continuous improvement.
• Develop high-quality Python and Java components for data processing, APIs, microservices, automation, integration and platform services.
• Engineer reliable batch and event-driven data pipelines with clear contracts, validation, observability, lineage
• and recoverability.
• Build AI-enabled solutions and reusable engineering accelerators, including agents, RAG patterns, tools,
• prompts, context packages, evaluations and guardrails.
• Apply specification-driven and AI-assisted development practices, using human approval gates for
• architecture, security, quality and production changes.
• Take a systems view of DVF, identifying cross-subsystem impacts, dependencies, bottlenecks, failure modes
• and opportunities to simplify the landscape.
• Challenge conventional approaches, rapidly prototype options and turn validated ideas into governed, reusable
• patterns and production solutions.
• Produce and maintain architecture views, technical designs, interface contracts, decision records, runbooks and implementation documentation.
• Implement automated unit, integration, contract, component, performance and regression tests as appropriate.
• Build and maintain CI/CD pipelines, Infrastructure as Code, security scanning, dependency management and quality gates.
• Ensure solutions meet requirements for security, privacy, data governance, information protection, auditability,
• resilience and operational support.
• Use telemetry and operational feedback to improve reliability, performance, cost efficiency and developer experience.
• Lead code reviews and technical design reviews, mentor engineers and promote consistent engineering standards and reusable solutions.
• Collaborate with Product Owners, Systems Analysts, Architects, Data Engineers, Test Engineers, Operations and Security to resolve ambiguity and deliver measurable outcomes.
• Support PI planning and sprint execution by refining technical work, identifying dependencies and risks, and
• providing realistic implementation options.
• Communicate technical decisions, progress, risks and trade-offs clearly to technical and non-technical stakeholders.
• Contribute to the evolution of DVF into an AI-native, federated data-product organisation with shared platform, quality and AI enablement capabilities.

QUALIFICATIONS/EXPERIENCE:

• Relevant degree or diploma in Computer Science, Software Engineering, Information Technology, Data
• Engineering or a related field.
• Typically, seven or more years of relevant software engineering experience, including responsibility for complex production systems.
• Demonstrable expert-level delivery using Python and/or Java, with strong data and integration engineering experience.
• Practical evidence of AI-assisted or AI-native engineering, including evaluation, governance and accountable human review.
• AWS, Java, Python, data engineering, architecture, DevOps, Kubernetes, Terraform, Agile or AI-related certifications are advantageous.