Posted on: 14/02/2026
Description :
- Advanced Logic : Deploy Few-Shot, Chain-of-Thought, and Structured Output techniques to
transform probabilistic models into reliable business tools.
- Efficiency : Optimize token usage to balance high performance with cost-effectiveness.
2. Evaluation & Reliability :
- Science-Based Testing : Move beyond "vibes" by conducting A/B testing and automated evaluations using frameworks like BLEU, ROUGE, or BERTScore.
- Guardrail Development : Build monitoring frameworks to proactively detect and neutralize hallucinations, bias, and irrelevance.
- Human-in-the-loop : Design feedback loops that allow human expertise to refine AI accuracy over time.
3. Collaborative Integration :
- Bridge the Gap : Partner with Data Scientists and Engineers to integrate prompts into RAG pipelines and production APIs.
- Knowledge Leadership : Maintain a reusable prompt library and mentor the broader team on LLM best practices.
Qualifications :
- Technical Fluency : Proficient in JavaScript, Python for automation, and a deep understanding of REST APIs, RAG Pipelines.
- Cloud Native : Hands-on experience with Azure OpenAI Service or similar enterprise-grade LLM platforms.
- The RAG Expert : You understand embeddings, vector search, and how retrieval improves model context.
Good To Have :
- Experience with Voice AI testing tools (e.g., Hamming AI, Cekura).
- Familiarity with Vector Databases like Pinecone, Weaviate, or Azure AI Search.
- A background in Cognitive Science or UX Writingyou understand how humans and machines process language.
Benefits :
- Flexible Working Hours.
- Hybrid Working Style.
- Personal Accidental Insurance.
- Health Insurance to Self, Spouse and two kids.
- 5 days working week.
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