Who is Authenticx? Authenticx is on a mission to help humans understand humans. Our software platform is the new standard for humanizing customer interaction data at scale. We do this by channeling our passion and talent into helping health care leaders listen to their conversational data in a way that delivers value to the enterprise. What do we offer our team members? <ul> <li>A culture based on our core values of Authenticity, Courage and Having Fun</li> <li>A collaborative environment that supports your personal and professional development</li> <li>Hybrid working flexibility&nbsp;</li> <li>Free health insurance options</li> <li>Comprehensive benefits - medical, vision, dental, life, and&nbsp;disability insurance</li> <li>HSA and&nbsp;FSA plans</li> <li>401(K)</li> <li>Unlimited vacation time</li> <li>Generous paid holidays, sick leave, and&nbsp;parental leave</li> <li>Perks at Work membership for discounts on shopping, travel and much more</li> </ul> Position Summary The AI Prompt Engineer will lead the design, development, and optimization of large language model (LLM) prompts used for scalable conversation scoring at Authenticx. This role is critical in translating objective scoring rubrics into reusable, testable prompt logic that supports our enterprise healthcare clients. The engineer will collaborate across teams including engineering, implementation, product, and data labeling to deliver reliable and high-quality prompt workflows. This is a hands-on role suited for someone who thrives in an experimental, iterative environment and has an interest in scaling natural language solutions.&nbsp; Key Responsibilities<span class="EOP SCXW67916979 BCX0" data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:281,&quot;335559739&quot;:281}"> <ul> <li>Design and implement sophisticated LLM prompts aligned to internal scoring rubrics and customer-specific needs.&nbsp; </li> <li>Conduct prompt testing and evaluation using labeled datasets to ensure performance accuracy.</li> <li>Collaborate with engineering to improve tooling and infrastructure for managing LLM scoring workflows.</li> <li>Maintain a centralized prompt library to ensure reuse and standardization across use cases.</li> <li>Document prompt strategies, testing approaches, and outcomes for internal learning.</li> <li>Identify and resolve inefficiencies in the prompt development and deployment process.</li> <li>Partner with product and data labeling teams to improve the quality and consistency of scoring outputs.&nbsp;</li> </ul> Required Qualifications <ul> <li>Strong understanding of LLMs, NLP systems, and prompt engineering concepts.&nbsp;</li> <li>Ability to structure and document complex logic in a scalable and repeatable manner.&nbsp;</li> <li>Demonstrated ability to collaborate effectively with both technical and non-technical teams.&nbsp;</li> <li>Analytical mindset with an interest in experimentation, iteration, and data-driven decision-making.&nbsp;</li> </ul> Preferred Qualifications <ul> <li>Experience in structured data labeling or QA workflows.&nbsp;</li> <li>Familiarity with tools like LangChain, OpenAI/GPT APIs, or vector databases.&nbsp;</li> <li>Background in linguistics, cognitive science, or HCI.&nbsp;</li> <li>Proficiency in Python or scripting tools for evaluation or automation.&nbsp;</li> </ul> Additional Information <ul> <li>May include occasional travel for team meetings or planning sessions</li> <li>Must be authorized to work in the U.S. without current or future visa sponsorship.</li> <li>This role will be hybrid based out of our Indianapolis office,&nbsp;</li> </ul> <span class="EOP SCXW67916979 BCX0" data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:281,&quot;335559739&quot;:281}">&nbsp;