Prompt Engineer

UNAVAILABLE; McLean (VA); On-site; USD 120,000 - 180,000; Full time

Job summary

UNAVAILABLE is seeking a Prompt Engineer to design, test, and refine interaction patterns for generative AI systems used across client engagements. You will shape how users experience AI-powered applications, ensuring outputs are relevant, safe, and aligned to mission needs.

You will collaborate with AI developers, LLMOps engineers, evaluation scientists, and design teams to craft prompts and improve retrieval strategies.

Qualifications

• Bachelor’s degree or higher in Computer Science, Linguistics, Cognitive Science, Data Science, or related discipline.
• 5+ years of total experience.
• 2+ years of AI/ML, NLP, content design, UX writing, or similar roles involving structured interaction design.
• Experience designing and testing prompts for LLMs in real applications (GPT-style models; Claude, Gemini, Llama, etc.).
• Familiarity with RAG architectures, vector databases, embeddings, and context retrieval strategies.
• Strong analytical skills to run structured experiments and document findings.

Responsibilities

• Design, iterate, and optimize prompts, templates, and prompt chains to improve accuracy, reasoning, and usability of AI outputs.
• Develop context management strategies including document selection, summarization, formatting, and retrieval augmentation patterns.
• Partner with developers to implement prompt engineering techniques within RAG pipelines, agentic workflows, evaluation harnesses, and application UX layers.
• Conduct structured experiments including A/B tests and rubric-based evaluations to measure prompt performance and identify improvement opportunities.
• Collaborate with AI Evaluation Scientists to define evaluation metrics tied to quality, relevance, consistency, safety, and hallucination reduction.
• Work with UX and product design teams to develop interaction flows that guide user inputs and reduce cognitive load.
• Translate complex subject-matter content into structured, LLM-friendly formats to improve system reasoning and reduce error rates.
• Support the design of safe output behaviors by implementing guardrails, filtering strategies, and context constraints aligned with governance principles.
• Document prompt patterns, style guides, failure modes, and best practices for internal reuse.
• Stay up to date on prompting strategies (CoT, self-critique, tool-use scaffolding, function calling, agentic behaviors) and share insights.

Skills

Prompt engineering

A/B testing

UX writing

Cross-functional collaboration

Communication

Problem solving

Structured experimentation

Education

Bachelor’s degree or higher in CS / Linguistics / Cognitive Science / Data Science or related

Tools

Python

LangChain

LlamaIndex

Job description

Overview

We are seeking aPrompt Engineer design, test, and refine interaction patterns for generative AI systems used across our client engagements. This role is central to shaping how users experience AI-powered applications and ensuring that LLM outputs are relevant, reliable, safe, and aligned to mission needs. The Prompt Engineer will work closely with AI Developers,LLMOpsEngineers, Evaluation Scientists, and product/design teams to craft prompts, structure context, improve retrieval strategies, and create intuitive multi-turn interaction flows.

Responsibilities

• Design, iterate, andoptimizeprompts, templates, and prompt chains that improve the accuracy, reasoning, and usability of generative AI outputs.
• Develop context management strategies, including document selection, summarization, formatting, role instructions, andretrievalaugmentation patterns.
• Partner with developers to implement prompt engineering techniques within RAG pipelines, agentic workflows, evaluation harnesses, andapplicationUX layers.
• Conduct structured experiments—including A/B tests and rubric-based evaluations to measure prompt performance andidentifyopportunities for improvement.
• Collaborate with AI Evaluation Scientists to defineevaluationmetrics tied to quality, relevance, consistency, safety, and hallucination reduction.
• Work closely with UX and product design teams to develop interaction flows that guide user inputs, clarify system capabilities, and reduce cognitive load.
• Help translate complex subject-matter content into structured, LLM-friendly formats that improve system reasoning and reduce error rates.
• Support the design of safe output behaviors by implementing guardrails, filtering strategies, and context constraints aligned with governance principles.
• Document prompt patterns, style guides, failure modes, and best practices for internal reuse and team enablement.
• Stay up to date on emerging prompting strategies (e.g.,CoT, self-critique, toolusescaffolding, function calling, agentic behaviors) and share insights with the team.
• You will contribute to the growth of our AI & Data Exploitation Practice!

Qualifications

• Ability to hold a position of public trust with the U.S. government.
• Bachelor’s degree in Computer Science, Linguistics, Cognitive Science, Data Science, ora relateddiscipline.
• 5+ years of total experience.
• 2+ years of experience in AI/ML, NLP, content design, UX writing, or similar roles involving structured interaction design.
• Demonstrated experience designing and testingprompts forLLMs in real applications (GPT-style models, Claude, Gemini, Llama, etc.).
• Familiarity with RAG architectures, vector databases, embeddings, and context retrieval strategies.
• Strong analytical skills with the ability to run structured experiments, analyze model outputs, and document findings.
• Proficiencywith Python and common AI frameworks (e.g.,LangChain,LlamaIndex) is preferred.
• Experience with UX design principles, information architecture, or conversational design is highly valuable.
• Understanding ofresponsible AI concepts, including safety, privacy, bias, and governance-aligned prompting strategies.
• Excellent written and verbal communication skills with the ability to translate domain-specific content into clear, effective AI instructions.
• Ability to collaborate across engineering, product, governance, and evaluation teams to shape coherent user-AI interactions.