Senior Software Engineer Job Johannesburg South Africa,Software Development

"At Klipboard we've introduced a flexible hybrid work policy, where employees spend three days in the office and two days working from home. This approach promotes a balanced work environment that combines office collaboration with the comfort and convenience of remote work."

Klipboard provides specialist software, services and support to deliver fully integrated trading and business management solutions to companies in the distributive trade – wherever they are in the world. With a unique depth of knowledge and experience in ERP/SaaS solutions, Klipboard has a wide range of clients includes wholesalers, distributors, merchants and retailers from small traders to multinational enterprises. Klipboard has offices in the UK, Ireland, The Netherlands, South Africa, Kenya and North America.

Our mission is simple: to design and deliver high performance, integrated ERP solutions that enable our distributive trade customers to source effectively, stock efficiently, sell profitably and service competitively

Klipboard is a global, growing business that embraces AI and emerging technologies to enhance customer outcomes, collaboration, and continuous improvement. We’re looking for people who are curious about or fluid with AI, open to change, and excited to learn how technology can improve the way we work and help our customers which is always supported by strong human insight and communication.

We are hiring a Senior Software Engineer to lead delivery on our C# / .NET products ( and Blazor) on Azure, and to help shape how the team builds software in an AI-native way. You’ll be expected to operate at the frontier of AI-assisted development — selecting tools, designing agentic workflows, integrating LLMs into our products, and coaching the wider team on getting safe, high-quality output from AI.

This is a technical leadership role: you will still be hands-on, but your impact extends through the engineers around you.

Key Responsibilities:

Lead the design and delivery of significant features and services on Azure

Set the technical bar in code review, architecture, testing, and security

Own and evolve our AI-assisted development practice — tooling choice, guardrails, prompt patterns, and team enablement

Design and build AI-enabled product features (copilots, RAG, summarisation, structured extraction, agents) using Azure OpenAI and related services

Drive Azure Dev Ops or Jira workflow, backlog shaping, and CI/CD pipeline design

Mentor mid-level and graduate engineers; raise the floor on AI tooling across the team

Engage with Product, QA, and Support on cross-cutting technical decisions

Lead incident response and root-cause analysis for production issues on your own

Skills, Knowledge and

Experience:

Core Technical:

Deep C# / .NET (including .NET Core /.NET 4.5 / .NET 8+), (ASPX), Xamarin Forms and Blazor in production

Win Forms with

WPF with C#.NET

XAML with MVVM Architecture

WCF (Windows Communication Foundation

Strong SQL Server and data modelling skills

SAP Crystal Reports

Component One Active Reports

Dev Express Controls

REST and SOAP Based API’s

Broad Azure experience (App Service, Functions, SQL, Storage, Key Vault, Service Bus, Application Insights)

Track record using AI coding assistants (Copilot, Cursor, or similar) to ship real, production-quality work — and the judgement to know their limits

Practical experience integrating LLMs into applications (Azure OpenAI, Semantic Kernel, Lang Chain, or equivalent)

Methodologies & Mindset:

Strong grasp of Agile delivery and SDLC

Deep, hands-on experience with Azure Dev Ops or Jira (boards, pipelines, release management)

Microservices, event-driven, and distributed systems design

Opinionated — pragmatically — on when AI accelerates delivery and when it creates risk

Collaboration & Communication:

Can lead a technical discussion and land on a clear decision

Effective mentor; gives high-signal code review feedback

Translates between engineering, product, and support audiences

Bonus

Skills:

RAG architectures, embeddings, vector stores (e.g., Azure AI Search), evaluation frameworks

Agentic / tool-using LLM patterns and their failure modes

Containers and AKS;
Infrastructure as Code (Bicep, Terraform)

Secur…