Prompt Engineer

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 Prompt 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