This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Prompt Systems Engineer based in the United States.
This is a hands-on AI engineering role focused on shaping how intelligent agents interact with learners, educators, and support teams.
You will own the design, testing, evaluation, and continuous improvement of prompts and system instructions powering AI agents across enrollment, learning, and student support.
Working at the intersection of AI capabilities and educational effectiveness, you will translate complex business and pedagogical requirements into reliable agent behavior.
You will collaborate closely with product managers, engineers, learning designers, and university stakeholders to build experiences that are accurate, useful, safe, and engaging.
The role combines prompt architecture, LLM evaluation, observability, red-teaming, RAG, and multi-turn conversational design.
You will also help establish reusable prompt engineering practices and quality standards as AI capabilities and model providers continue to evolve.
This is an opportunity to have a direct impact on the future of digital education within a collaborative, fast-moving, and highly innovative environment.
Accountabilities
- Design, write, iterate, test, and maintain system prompts and instruction sets for AI agents supporting student enrollment, learning, retention, and student services.
- Translate complex educational, operational, and business requirements into precise agent behavior, including personas, tone, scope constraints, fallback handling, and multi-turn conversation logic.
- Design prompt architectures for multi-step and chained agent workflows, including Retrieval-Augmented Generation (RAG) experiences using program-specific knowledge bases.
- Collaborate with engineering teams to configure and deploy agents through an AI orchestration platform, including primary prompts, secondary context, knowledge-base attachments, and embed definitions.
- Design conversational experiences involving learners, campus or support staff, and AI assistants working together.
- Build and maintain evaluation frameworks that measure agent accuracy, tone, hallucination rates, task completion, and alignment with rubric-based learning objectives.
- Use LLM observability platforms such as Langfuse to monitor production performance, identify regressions, and prioritize improvements.
- Develop red-team and adversarial testing approaches to uncover edge cases, risks, and failure modes before agents are deployed to learners.
- Establish prompt versioning practices and maintain a library of tested, reusable prompt components.
- Partner with product, learning, enrollment, student success, engineering, and university stakeholders to design, build, test, and continuously improve AI agents.
- Translate learning objectives, operational workflows, rubric assessments, and program-specific requirements into effective prompt-level instructions.
- Tune companion agents for individual programs and educational partner contexts.
- Develop and document prompt engineering guidelines, standards, and best practices for internal teams.
- Monitor changes in capabilities across OpenAI, Anthropic, and other model providers, proactively identifying opportunities, limitations, and risks.
- Contribute to prompt automation, evaluation, and testing workflows using lightweight code where appropriate.
Requirements
- 2+ years of experience designing and iterating on prompts for production LLM-powered applications.
- Deep familiarity with prompt engineering patterns, including few-shot examples, system and user roles, reasoning-oriented prompting, output constraints, tool-use prompting, and RAG integration.
- Exceptional written communication skills, with the ability to express complex requirements clearly, precisely, and persuasively.
- Hands-on experience creating and running prompt evaluations, including defining metrics, developing test cases, analyzing results, and making data-informed improvement decisions.
- Ability to collaborate effectively across technical and non-technical disciplines, from discussing context windows and APIs with engineers to translating educational frameworks and learning objectives with faculty or learning specialists.
- Experience with LLM observability platforms such as Langfuse, Weights & Biases, or similar tools.
- Familiarity with Learning Tools Interoperability (LTI) and the integration of AI tools with learning management systems such as Moodle, Canvas, or Instructure.
- Experience with voice agents, multimodal prompting, or other emerging AI interaction modalities is a plus.
- Ability to read and write basic JavaScript or Python to support prompt automation, experimentation, and testing pipelines.
- Working knowledge of OpenAI, Anthropic, or comparable model-provider APIs.
- Strong analytical and problem-solving skills, with the ability to identify failure modes and continuously improve AI behavior.
- Ability to thrive in ambiguity, experiment rapidly, and incorporate user feedback into iterative improvements.
- Strong organizational and collaboration skills in a dynamic, rapidly evolving, team-based environment.
- A genuine interest in applying AI to improve learning, enrollment, student success, and educational experiences.
- Applicants must be legally authorized to live and work in the United States and must reside within the United States for the duration of employment.
Benefits
- Competitive annual salary of $100,000–$120,000.
- Fully remote work, with the option to work from a New York City office.
- Company-provided computer and charger.
- 401(k) plan with company matching.
- Equity opportunities.
- Medical, dental, and vision insurance for employees and families.
- Mental health resources, including access to Headspace and Talkspace.
- Employer-paid life and disability insurance.
- Optional supplemental life, accident, critical illness, and hospital insurance.
- Health Savings Account (HSA) and Flexible Spending Accounts (FSA).
- Commuter benefits and additional pre-tax benefit options.
- Employee Assistance Program (EAP).
- Paid parental leave.
- Wellness programs and resources.
- Free Calm app subscription.
- Employee discount program.
- Four weeks of paid vacation.
- 10 paid holidays plus paid sick leave.
- Monthly mobile connectivity stipend.
- Annual education stipend supporting lifelong learning.
- Opportunities for professional growth, development, and career progression.
- Inclusive, collaborative workplace culture that values diverse perspectives and backgrounds.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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