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Prompt Engineer

Job in New York, New York County, New York, 10261, USA
Listing for: Inizio Partners Corp
Full Time position
Listed on 2026-05-03
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Location: New York

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
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