Lead AI Engineer

Scrums.com is looking for a Lead AI Engineer, Voice AI and LLM Systems to help shape their client’s next-generation voice and LLM platform for contact centre and collections operations.This is a hands-on leadership position. You’ll help lead a small team while owning live voice agents and speech pipelines that real customers use at high call volumes. You’ll take systems that already work in production and scale them to new clients, languages and channels, including email and WhatsApp. You’ll work directly with the Head of AI on architecture and priorities, with real influence over how the platform grows. It suits a high-agency engineer who spots what needs doing, takes ownership and ships it without waiting to be told.The position is full time and onsite in Sandton, Johannesburg.

Responsibilities

• Build and improve real-time voice agents, including prompts, tool calling, webhooks and telephony integration.
• Own the speech and LLM pipelines: transcription, diarization, voice activity detection (VAD) and LLM-based call scoring.
• Build and maintain evaluation suites, including LLM-as-judge and regression tests running in CI.
• Drive latency, reliability and cost, including GPU and LLM spend, failure handling and observability.
• Ship production Python services on Azure (Functions, Kubernetes, queues and SQL).
• Help build new channels: email and WhatsApp agents, post-call summaries and outcome scoring.
• Work with the Head of AI on architecture, priorities and production risk.
• Mentor and review other engineers while staying hands-on.

Experience and education

• 6+ years of software engineering experience, including at least 2 years building LLM or speech AI systems in production.
• A track record of shipping AI products that real users and businesses depend on, not just prototypes.
• Experience leading or mentoring engineers while remaining hands-on.
• Strong Python, with hands-on experience of LLM platforms and serving (Azure OpenAI, OpenAI, vLLM).
• Experience with speech tooling: speech-to-text, text-to-speech, Whisper, diarization and VAD.
• Experience running services on Azure, with Docker, Kubernetes, CI/CD (Azure DevOps) and observability (Application Insights, Grafana).
• Advantageous: contact centre, collections, fintech or other regulated environments.
• Preferred: a degree in Computer Science, Engineering or similar, although a proven production track record matters more.