Ready to take the lead in building the next generation of AI-powered solutions?
This is an exciting opportunity for a Lead AI Engineer to join a dynamic technology environment where cutting-edge AI is being turned into real-world, production-ready solutions. You’ll work across LLMs, voice agents, speech technologies, automated testing, AI coding tools, and modern software development practices, while taking ownership of key technical initiatives and helping shape the future of conversational AI.
If you’re a hands-on technical leader who enjoys solving complex engineering challenges, mentoring others, and turning innovative ideas into scalable production systems, this could be the opportunity you’ve been looking for.
Must-have skills and experience:
7+ years software engineering, 3+ years shipping LLM and/or speech+LLM systems to productionStrong production PythonDeep experience in at least two of: voice/conversational agents, speech pipelines (STT/diarization/VAD), LLM evaluation, multi-agent/tool-calling systemsSolid Azure experience (serverless and/or Kubernetes, queues/messaging, blob storage, SQL, secrets/identity)Prompt engineering for multi-step, compliance-sensitive workflowsProven player-coach leadership in a small agile teamStrong advantages:
Experience with AI coding assistants such as Cursor, Claude, or similarVoice platform experience and STT/TTS vendor tuningWhisper / diarization / vLLM / OpenAI Batch / structured outputsContact-centre, collections, or BPO domain experienceObservability (Application Insights, Grafana) and CI/CD collaborationWhatsApp / email bot experienceResponsibilities:
Own end-to-end delivery for one or more major areas (voice agents, speech/LLM QA pipelines, post-call intelligence, or text-channel agents)Partner with the head of AI on architecture, priorities, and production risk; turn decisions into shipped systemsDesign and build production Python services on Azure (Functions and/or Kubernetes workers, messaging, storage, SQL-backed outcomes)Lead prompt/agent design, structured LLM outputs, evaluation/regression suites, and operational reliability (latency, cost, failure handling, observability)Drive post-call intelligence quality: scoring accuracy, structured output reliability, and pipeline performanceMentor senior → Junior engineers through design reviews, pairing, and code reviewCollaborate with the platform portal team so campaigns, dashboards, and QA surfaces stay aligned with the AI runtimeWork with Azure DevOps on deployability, GPU/LLM cost trade-offs, and production operationsReference number for this position is GZ61522 which is a permanent position based in Sandton offering a salary of R1.5m per annum, negotiable based on experience and ability.
Contact Garth on [[garthz@e-merge.co.za]] or call 011 463 3633 to discuss this and other opportunities.
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