Prompt Engineer

Moonfire; Jersey City (NJ); On-site; USD 90,000 - 120,000; Full time

Job summary

Moonfire based in Jersey City, New Jersey, is hiring for a role focused on designing, testing, and optimizing prompts for various AI applications. Candidates should have a strong understanding of LLM behavior and hands-on experience with OpenAI APIs among other platforms.

The ideal applicant will be responsible for ensuring the accuracy and compliance of model outputs while collaborating with engineering teams. Candidates with a background in NLP or technical writing are preferred.

Qualifications

• 4+ years of experience in LLM behavior and prompt design.
• Hands-on experience with OpenAI APIs and similar platforms.
• Strong writing, analytical, and stakeholder-management skills.

Responsibilities

• Design prompts for various AI systems including chatbots and summarization tools.
• Optimize prompts for performance and compliance.
• Evaluate performance using relevant metrics.

Skills

Understanding of LLM behavior

Prompt design

OpenAI APIs

Analytical skills

Communication skills

Tools

Azure OpenAI

LangChain

LlamaIndex

Job description

Job Summary

Design, test, govern, and continuously improve prompts, system instructions, conversation flows, and interaction patterns for LLM applications. The role ensures model outputs are accurate, grounded, safe, consistent, cost‑aware, and aligned with business and compliance expectations.

Key Responsibilities

• Design prompts for chatbots, copilots, RAG systems, document analysis, summarization, workflow agents, and knowledge assistants.
• Develop system prompts, few‑shot examples, tool‑use instructions, response formats, escalation logic, and conversation policies.
• Optimize prompts for accuracy, relevance, groundedness, tone, compliance, latency, token efficiency, and repeatability.
• Build reusable prompt libraries and templates aligned to enterprise standards and business domains.
• Evaluate prompt performance using metrics such as task success, groundedness, hallucination rate, completeness, safety, and user satisfaction.
• Partner with engineers to implement prompt versioning, testing, deployment, and monitoring in production systems.
• Support RAG quality by assessing retrieval context, chunking quality, source citation behavior, and response synthesis.
• Conduct adversarial testing for prompt injection, jailbreaks, instruction conflicts, sensitive‑data leakage, and unsafe outputs.

Required Qualifications

• 4+ Years of Strong understanding of LLM behavior, prompt design, tokenization, context windows, RAG, embeddings, and model limitations.
• Hands‑on experience with OpenAI APIs, Azure OpenAI, Anthropic, LangChain, LlamaIndex, Semantic Kernel, or similar platforms.
• Ability to debug LLM outputs using structured testing, error analysis, and iterative refinement.
• Strong writing, analytical, communication, and stakeholder‑management skills.
• Understanding of prompt‑security risks including prompt injection, jailbreaks, data leakage, and hallucination.

Preferred Qualifications

• Background in NLP, conversational AI, UX writing, technical writing, product design, knowledge management, or business analysis.
• Experience in financial services, legal, compliance, risk, operations, customer support, or enterprise knowledge domains.
• Familiarity with prompt registries, A/B testing, human review workflows, and evaluation tooling.