Prompt Engineer

Steampunk•McLean, VA

1d•$115,000 - $140,000

About The Position

We are seeking a Prompt 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, LLMOps Engineers, Evaluation Scientists, and product/design teams to craft prompts, structure context, improve retrieval strategies, and create intuitive multi-turn interaction flows.

Requirements

Ability to hold a position of public trust with the U.S. government.
Bachelor’s degree in Computer Science, Linguistics, Cognitive Science, Data Science, or a related discipline.
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 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 with the ability to run structured experiments, analyze model outputs, and document findings.
Proficiency with Python and common AI frameworks (e.g., LangChain, LlamaIndex) is preferred.
Understanding of responsible 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.

Nice To Haves

Experience with UX design principles, information architecture, or conversational design is highly valuable.

Responsibilities

Design, iterate, and optimize prompts, 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, 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 opportunities for improvement.
Collaborate with AI Evaluation Scientists to define evaluation metrics 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, tool use scaffolding, function calling, agentic behaviors) and share insights with the team.
You will contribute to the growth of our AI & Data Exploitation Practice!