Technology
Prompt Engineer
Inizio Partners Corp
HimalayasRemote
- Location
- United States, United States
- Type
- Remote
- Salary
- Salary not specified
- Posted
- 2 Nov 2026
Role & Responsibilities Overview:• Prompt Design & Optimization • Design prompts for - summarization, risk insights, adverse media analysis, underwriter assistant agent etc.
Role & Responsibilities Overview: Prompt Design & Optimization Design prompts for - summarization, risk insights, adverse media analysis, underwriter assistant agent etc. duplicate explanation, decision support Optimize prompts for accuracy, grounding, and consistency Evaluation & Continuous Improvement Define evaluation scenarios and validation datasets Use LLM-as-judge and feedback loops to improve responses Continuously refine prompts based on - model performance, user feedback RAG & Assistant Enablement Work with AI engineers to - improve retrieval quality, design context injection strategies Ensure outputs are – grounded, explainable, aligned with underwriting logic Business Alignment Translate underwriting workflows into prompt logic Incorporate domain-specific language, risk indicators, and business rules Collaborate with underwriters and SMEs P rompt Governance Maintain prompt library and versioning Define templates for different LOBs and use cases Ensure consistency across assistant and workflows Candidate Profile: Experience: 5–8+ years with 2–4+ years in GenAI / prompt engineering Domain (Mandatory): Strong insurance / underwriting knowledge Education: Bachelor's/Master's in Engineering, Data Science, Business Analytics, or related Profile Type: Hybrid business + technical, strong analytical thinker Technical skills : GenAI & Prompting - prompt engineering techniques (few-shot, chain-of-thought, structured prompts);Experience with Azure OpenAI / LLM APIs; Prompt versioning and optimization RAG & Retrieval Awareness - understanding of Azure AI Search and retrieval behavior; Context design and grounding strategies; Ability to reduce hallucinations via prompt + retrieval design Evaluation & Quality - LLM-as-judge / evaluation frameworks; Output validation and benchmarking; A/B testing of prompts Safety & Governance - Awareness of guardrails (NeMo Guardrails); PII handling (Presidio); Responsible AI practices Collaboration & Tools - Familiarity with APIs, JSON, and structured outputs; Basic Python; Working with AI engineers and data teams Originally posted on Himalayas