Senior Technical Software Engineer - AI Platforms

In this role, you will:

• Collaborate with the team to deliver technical design, development and deployment of complex solutions within relevant product.
• Carry out effective technical design reviews to ensure that the right architecture patterns are used by the team.
• Drive the adoption of Engineering practices, implement development process automation, lean software development, built-in-quality, test driven development, agile practices, and timely root cause analysis and blameless incident post-mortems.
• Partner with cross-functional teams to determine viability of solutions.
• Evaluate current problems, future requirements and existing solutions in medium to large projects to enable high level design and drive proof-of-concepts and implement prototypes to validate ideas.
• Investigate, debug and fix complex issues involving corner cases and rare conditions.
• Support continuous improvement by investigating alternatives and new technologies and presenting these for architectural review.
• Contribute to sprint/work design and planning by providing subject matter expertise on business domain and relevant technologies and actively contribute to technology specific community of practices.
• Manage and mentor Software Engineers to allow for skill/knowledge development through advice, coaching, and training opportunities. Responsible for their technical deliveries and adherence to design and coding standards and practices.
• Ensure optimal use of enterprise application platforms, tools and libraries in line with the approved technology architecture.
• Responsible for corrective, adaptive, preventative and perfective maintenance of products in collaboration with other capabilities for the relevant product.

Desired Candidate Profile

• Degree or Honours (12+3 or equivalent).
• Minimum of 5+ years of experience in Information Technology.
• Experience of developing advanced/complex technology Software solutions for large, complex organisations in a multi-functional environment.
• Experience developing and/or integrating AI solutions, whether through in-house development or leveraging managed AI services
• Practical experience building with LLMs, SLMs and open-weight models prompt engineering and caching, RAG/vector search, MCP-based tool integration, agent frameworks, evaluation and tracing/observability of AI applications in production.
• Hands-on, demonstrable experience with AI services on at least one hyperscaler - AWS (Bedrock, SageMaker), Azure (AI Foundry/Azure OpenAI, AI Search) or GCP (Vertex AI, Gemini) - with experience across two or all three considered a strong advantage.
• Experience with agent/orchestration frameworks (e.g. LangGraph, LlamaIndex, Semantic Kernel, Strands, ADK) and building MCP servers.
• Understanding of responsible AI and AI security fundamentals guardrails, content filtering, prompt-injection and data-leakage risks, grounding and citation to reduce hallucination, and safe handling of secrets, PII and model access.
• Exposure to full stack development across UI, middleware and databases, sufficient to integrate AI capabilities end to end.

Nice to have:

• Experience with evaluation and observability tooling for AI (e.g. LangSmith, Langfuse, Ragas, Arize, Azure AI Evaluation).
• Relevant cloud certification (AWS ML/AI, Azure AI Engineer Associate, Google Cloud ML Engineer).
• Experience fine-tuning or self-hosting open-weight models (e.g. Llama, Mistral, Qwen) and understanding of when small models are the better fit.