Prompt Engineer (llms / RAG / Edtech)

Prompt Engineer (LLMs / RAG / EdTech)

Tech9 is shaking up a 20-year-old industry — and we're not slowing down. Recognized by Inc. 5000 as one of the nation's fastest-growing companies, ranked #23 among Utah's fastest-growing companies, and named one of Forbes' Top 500 Startup Companies to Work For (two years running), we're redefining what it means to build world-class software and AI-driven solutions. We invite you to interview with us, show us what you can do, and discover how Tech9 can give you the AI-forward career opportunity you've been looking for.

About The Role

We are partnering with a client seeking a highly skilled Prompt Engineer with deep expertise in LLM systems, structured prompt design, and simulation-driven learning environments. This role sits at the intersection of product, pedagogy, linguistics, psychology, and applied AI — ideal for someone who understands both the creative and technical sides of LLM-powered learning experiences. You'll collaborate with simulation designers, AI engineers, and learning architects to craft structured prompts, evaluation frameworks, and RAG pipelines that power sophisticated learning simulations and human-interaction scenarios.

Responsibilities

• Design, structure, and refine high-quality prompts for complex, production LLM environments.
• Implement and maintain RAG pipelines, ensuring accurate retrieval and structured JSON outputs.
• Build evaluation rubrics, prompt datasets, and testing frameworks to measure output quality and alignment.
• Translate learning objectives and human-to-human scenarios into effective prompt-driven AI behaviors.
• Serve as the connective tissue between creative teams (simulation designers, instructional writers) and technical AI engineers.
• Lead prompt ideation, prototyping, testing, iteration, and deployment.
• Apply principles from linguistics, cognitive psychology, learning design, and communication modeling to improve prompt quality.
• Contribute to evolving prompt engineering processes, tools, and best practices for scalable delivery.

Minimum Qualifications

• 3+ years of US-based EdTech experience.
• 1–3+ years in AI/ML or product roles directly involving LLM systems.
• Demonstrated expertise designing prompts for production LLMs (OpenAI, Claude, Gemini, etc.).
• Strong understanding of RAG architectures, evaluation datasets, and structured outputs (JSON).
• Background in linguistics, psychology, learning design, or communication modeling (strong plus).
• Ability to bridge creative and technical domains, working effectively with writers, designers, and engineers.
• Comfort working in ambiguity, rapidly prototyping, and iterating based on performance data.
• Familiarity with learning platforms, behavior modeling, or communication simulations.

Nice To Have

• Experience with simulation platforms or virtual learning environments.
• Experience designing psychological rubrics or scenario-based learning journeys.
• Exposure to working with voice actors, scriptwriters, or narrative teams.

What You'll Love About Tech9

At Tech9, we prioritize freedom, flexibility, and craftsmanship. When you join us, you can expect:

• Opportunities to work on meaningful, cutting-edge AI experiences.
• Autonomy to shape prompt design and AI behavior.
• A collaborative, supportive environment with talented teammates.
• No unnecessary bureaucracy — just what you need to succeed.

Interview Process

Our interview process moves efficiently while ensuring clarity and alignment:

1. Introductory Call- Quick conversation with our recruiting team to understand background and alignment.
2. On-Demand HireVue Screening- Behavioral and situational questions to learn how you communicate and work through ambiguity.
3. Internal Technical Interview- Deep dive into prompt engineering fundamentals, LLM design patterns, RAG reasoning, and structured output thinking.
4. Client Technical Interview #1- Scenario-based problem solving focused on LLM behavior shaping, evaluation methods, and simulation logic.
5. Client Technical Interview #2- Applied technical discussion on RAG pipelines, structured prompts, and real-world production examples.
6. Client Culture Fit Interview- Conversation with client stakeholders to ensure team alignment, collaboration style, and communication fit.

Additional steps may be added if needed.