Minimum 1–2 years of hands-on experience in prompt engineering, conversational-AI / chatbot design, NLP, or a closely related role. Candidates with strong, demonstrable project work and shorter formal tenure may be considered.
Demonstrated experience designing and deploying prompts or dialogue flows for production LLM or voice-bot systems — not solely experimental or academic work.
Track record of tuning and evaluating prompts against measurable KPIs and running structured A/B tests to improve real-world outcomes.
Prior exposure to contact-centre, telephony, or IVR environments, ideally in collections, customer service, or financial services.
Experience in or alongside debt collections, lending, fintech, BPO, or banking operations is a strong advantage.
Experience collaborating with cross-functional teams (IT, strategy, operations) and managing third-party AI / voice-vendor relationships is desirable.
Experience producing English- and Swahili-language conversational content for a Kenyan or East African customer base is highly desirable.
Education & Certifications
Bachelor's degree in Computer Science, Software Engineering, Computational Linguistics, Data Science, or a related field. Equivalent, demonstrable hands-on experience in prompt engineering or conversational AI will be considered in lieu of a degree.
A reviewable portfolio of production prompt work — prompt libraries, system prompts, evaluation harnesses, or published repositories — that can be walked through at interview.
Certification in Google Cloud (Vertex AI / Generative AI), OpenAI, or an equivalent LLM / conversational-AI program is an added advantage.
Technical Skills
Hands-on command of core prompt-engineering techniques: system and role prompting, few-shot and chain-of-thought design, delimiter and Markdown structuring, output schema and constraint control, and guardrail / fallback design.
Working proficiency with at least one major LLM platform — Google Gemini (AI Studio / Vertex AI) and/or OpenAI GPT-4o — including parameter tuning (temperature, max_tokens, top-p, streaming) and a practical grasp of tokenization and context-window economics.
Understanding of voice-AI pipelines — automatic speech recognition (ASR) and text-to-speech (TTS) — and how transcription accuracy, latency, and barge-in behaviour affect live call performance.
Familiarity with IVR / telephony concepts: Webitel or comparable contact-centre platforms, SIP trunking, call routing, and API-based integrations.
Ability to read and reason about JSON API request/response payloads and to work in API consoles (e.g., Postman). Basic scripting in Python or JavaScript for prompt testing and batch evaluation is an advantage.
Competence in designing and interpreting A/B tests and quantitative metrics — latency, containment, promise-to-pay rate, recovery rate, and cost-per-call.
Language & Domain Knowledge
Full professional fluency in English and Swahili, with the ability to author, review, and QA bot dialogue and call scripts in both languages.
Awareness of debt-collections conduct standards and Kenyan consumer-protection and data-privacy obligations, including the Data Protection Act, 2019 and CBK consumer-protection expectations.
Personal Attributes
Strong analytical and problem-solving mindset with meticulous attention to detail.
Comfortable with ambiguous requirements and rapid, data-driven iteration.
Clear written and verbal communicator who can translate technical findings for non-technical stakeholders.
Self-driven and organised, able to maintain a versioned change log across multiple concurrent campaigns.
GK
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