Introduction Our client is seeking an advanced full-stack software engineer to join an Intelligent Document Processing (IDP) platform team.
In this role, you will work across the entire stack—from modern Angular frontends to serverless Python backends running on AWS—building multi-tenant cloud platforms that ingest, interpret, and validate high-volume enterprise document workflows.
✅ Advanced full-stack engineering with modern Angular and cloud-native Python
✅ Hybrid and remote working flexibility with 1960 flexible annual hours
✅ High-ownership role driving AWS serverless architecture, event-driven pipelines, and AI platform tools
POSITION: Contract: 01 June 2026 – 31 December 2028 EXPERIENCE: 4-6 years related experience COMMENCEMENT: 01 June 2026 LOCATION: Hybrid: Midrand/Menlyn/Rosslyn/Home Office rotation TEAM: Software Engineering / Intelligent Document Processing & AI Platforms
Duties & Responsibilities Role Requirements
Design and deliver full-stack features across modern frontends and serverless backends within a multi-tenant document processing platform. Build and maintain reliable APIs and backend services, owning API contracts, performance, and the developer experience. Architect and implement high-throughput, event-driven processing pipelines to handle document ingestion and interpretation at scale. Own and evolve reusable Infrastructure-as-Code modules across development, staging, and production environments with software development rigor. Lead technical design reviews and establish engineering standards for code quality, testing frameworks, and deployment gates. Collaborate closely with product owners, data scientists, and platform engineers to translate core goals into scalable solutions. Mentor and support engineers at all levels through code reviews, pair programming, and architectural knowledge sharing. Champion CI/CD excellence by continuously optimizing test automation and deployment confidence. Embed end-to-end security into the platform, including robust access controls, encryption, infrastructure compliance, and vulnerability scanning. Drive system observability and operational reliability through custom monitoring, alerting, and proactive incident management. Contribute to AI-powered feature development, including integration with LLMs and enterprise document intelligence services. Act as a trusted technical advisor to evaluate emerging technologies and recommend improvements aligned with long-term platform roadmaps.
Please Note:
South African citizens/residents preferred.
Valid work permit holders will be considered.
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Desired Experience & Qualification Qualifications / Experience
Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field, or equivalent demonstrable experience building production-grade cloud platforms 6+ years of professional software engineering experience with a strong full-stack track record—taking features and platforms from zero to production at scale Proven experience delivering complex, distributed architectures on a major cloud platform with Infrastructure-as-Code, including leading cross-functional technical initiatives from design through production
Level Criteria
Communication: Adapt (Reach agreement through flexibility and compromise. The parties generally have the same objective). Delivery: Delivery is sometimes unclear and may require the employee to seek clarity and adapt requests to be aligned to business standards. Employee may be expected to provide guidance to lower level employees. Knowledge: Expertise in a specific field or discipline with multiple experiences where practical implementation has been merged with technical theory. Problem Solving: Check that the solutions by others are addressing the problems identified. May need to develop simple solutions to varied problems in single systems. Supervision: Mostly autonomous with a mentor on tasks that require senior involvement.
Essential Skills Requirements
Deep experience with modern frontend frameworks (Angular or equivalent) and TypeScript, focusing on fast, accessible, and maintainable UIs. Strong Python programming skills with a track record of building cloud-native serverless backends running reliably in production. Full-stack engineering depth with particular strength in backend systems: databases, APIs, authentication, reliability, and infrastructure. Experience designing and operating production workloads on AWS at scale, with an understanding of trade-offs between services, cost, and complexity. Deep understanding of Infrastructure-as-Code (IaC) with experience managing deployments across multiple environments from dev through production. Proven experience building and operating platforms that serve many concurrent users reliably. Comfort with ambiguity and ownership; ability to translate business intent into technical architecture without heavy specification. Competence with containerization, CI/CD, and DevOps practices (Docker, ECS, Kubernetes) to maintain a smooth path to production. Experience interfacing with security and infrastructure teams to meet organizational compliance requirements while maintaining velocity. Active use of AI tools in engineering workflows and a genuine curiosity about how AI is changing software platform capabilities.
Advantageous Skills Requirements
Experience designing systems that non-technical users can configure and operate without engineering bottlenecks. Prior background at a high-growth company building platform infrastructure relied upon by other teams. Familiarity with building systems that incorporate LLM capabilities as core infrastructure. Familiarity with agentic AI patterns, prompt engineering, or LLM orchestration frameworks. Understanding of data science workflows, ML model integration, or intelligent document processing pipelines. Experience building or operating multi-tenant SaaS platforms with per-tenant isolation and configuration. Exposure to enterprise design systems or component libraries at scale. A thoughtful approach to testing strategy (unit, integration, and end-to-end automation) and experience shaping team testing culture. Experience building orchestration workflows for complex, asynchronous processing at scale. Foundational understanding of responsible AI, safety, and guardrails for LLM-powered applications.
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