Job Title: AI Engineer Location: NYC, NY | Atlanta, GA | Remote, USA Exemption Status: Full-time, exempt Who We Are Impiricus is the first and only AI-powered HCP Engagement Engine. In 2025, Deloitte named Impiricus the #1 fastest growing company in North America for their prestigious Fast 500 list. Founded by a practicing physician and a senior pharmaceutical executive, Impiricus was created to transform how life sciences companies support physicians. We ethically connect HCPs to pharma resources, reduce go-to-market costs and accelerate patient access to the treatments they need. With our unique access to the largest opted-in network of HCPs, their insights, and clinical expertise, we are the leading provider of AI technology and real-time channels that life science companies need to deliver clear, reliable, and evidence-based resources directly into the hands of HCPs. Guided by a council of 2000+ trusted HCP advisors, we ensure every interaction is clinically meaningful, ethically grounded and leads to better patient care. Job Summary We’re seeking a highly technical and hands-on AI Engineer to join our growing team. This role will focus on designing intelligent LLM interaction pipelines, and integrating generative AI solutions into our platform. You’ll work closely with both our in-house engineering team and offshore developers, contributing directly to AI-driven features while helping manage project deliverables and team coordination. This role is ideal for a builder who thrives in fast-paced environments and wants to make a tangible impact by bringing real-world AI applications to life. We’re looking for someone who is deeply technical, passionate about AI development, and eager to grow into a leadership role as the AI team scales. Responsibilities - Integrate AI-driven functionalities and APIs into our product - Implement prompt engineering, Retrieval-Augmented Generation (RAGs), and basic generative AI solutions into platform workflows - Collaborate on AI model deployment, fine-tuning, and production integration - Apply ML algorithms such as linear regression, logistic regression, tree-based methods, and neural networks where applicable - Collaborate closely with offshore development teams to ensure timely and effective task execution - Ensure scalable, secure architecture leveraging AWS services (EC2, S3, Lambda, etc.) - Contribute to architectural decisions, backend infrastructure, and system optimization - Work cross-functionally with product, data science, and engineering teams to align AI initiatives with business goals - Mentor junior engineers as the team grows - Stay current with emerging AI technologies and assess their applicability to product needs Requirements - Bachelor’s degree in Computer Science, Mathematics, Physics, or a related STEM field - 3+ years of backend software development experience, with strong AI/ML focus - Experience with generative AI technologies, including prompt engineering and API integrations - Solid understanding of ML algorithms (regression models, tree-based algorithms, neural networks) - Proficiency with AWS infrastructure (EC2, S3, networking fundamentals) - Strong foundation in general computer engineering and networking principles Nice-to-Have - Experience with AI research projects (e.g., public health AI applications, LLM fine-tuning) - Background in computer architecture (CUDA, GPU parallelization, compute optimization) - Familiarity with healthcare data is a plus, but not required - Experience working in high-growth tech companies or research labs The base salary range for this role is $140,000 - $170,000. Where you land within the range will reflect your skills, experience, and location, while keeping team parity in mind and leaving room for future growth. Important Notice To protect candidates, please note that all communication from our team will come directly from an @impiricus.com email address. We do not engage third party recruiters to schedule interviews for this role. If you receive outreach from anyone outside of our domain claiming to represent Impiricus, please disregard and let us know by forwarding the message to careers@impiricus.com Benefits Impiricus focuses on taking care of our teammates’ professional and personal growth and well-being. Healthcare: Medical, dental, and vision coverage for you and your dependents + on-demand healthcare concierge HSA, FSA & DCFSA: Pre-tax savings options for healthcare and dependent care, with monthly employer contributions to HSA (if enrolled in a high-deductible plan) Coverage & Protection: 100% paid short- and long-term disability, plus life and AD&D insurance Flexible Time Off: Take the time you need with a flexible vacation policy — recharge your batteries your way Parental Leave: Paid parental leave to spend time with your newborn, adopted, or foster child (available after 6 months) Your Work, Your Way: If you’re close to an office, we encourage spending some time in-person to collaborate and connect. If not, remote is always an option. Home Office Setup: We’ll ship you the gear you need to create a comfortable workspace at home. 401(k): Save for your future with tax advantages (and company match!) Impiricus provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

About Us Pearl is AI for professional services at global scale, combining advanced AI with verified human expertise to deliver help that is accurate, accountable, and fast. Since 2003, our network has connected millions of customers with licensed professionals across 196 countries, making real expertise available anytime, anywhere. Our Values - Data driven: Data decides, not egos - Courageous: We take risks and challenge the status quo - Innovative: We're constantly learning, creating, and adapting - Lean: We focus on customers, using lean testing to learn how to serve them best - Humble: Past success is not a guarantee of future success About the Role We are seeking an AI Prompt Engineer II who combines strategic thinking, scientific expertise, and hands-on building skills. You will join a dynamic, agile team dedicated to designing, testing, and scaling large language model (LLM) prompts that drive impactful user experiences. Leveraging your deep knowledge of Generative AI, you will enhance our AI-powered expert platform, unlocking meaningful business outcomes and shaping how AI understands customers and supports experts. What You’ll Do - Design, build, and develop AI agents - Create complex multi-part prompting systems with parameter optimization and implement advanced prompting techniques - Develop comprehensive evaluation frameworks to measure performance across multiple dimensions, comparing approaches such as retrieval-augmented generation (RAG), fine-tuning, and advanced prompting methodologies - Analyze and optimize LLM performance using A/B testing, usage metrics, and strategic feedback loops - Develop AI-driven workflows that improve user interactions and Customer Care support - Design and refine expert playbooks to enhance knowledge sharing and operational efficiency - Run experiments to validate ideas rapidly and iterate based on performance data and user insights - Collaborate cross-functionally with product managers, engineers, and stakeholders to identify LLM opportunities and translate technical capabilities into business value - Manage stakeholder expectations and communicate complex technical concepts effectively to both technical and non-technical audiences - Implement LLMOps best practices including model governance, lifecycle management, and performance monitoring to ensure production-ready AI systems - Educate and empower internal teams to build better prompts and leverage AI tools effectively What We’re Looking For - Master’s or PhD in Computer Science, Computational Linguistics, Machine Learning, or a related field preferred - Strong proficiency in Python with hands-on experience building and testing complex prompting systems - Deep understanding of LLMs and advanced frameworks, with expertise across multiple LLM vendors and model versions - Proven experience developing and applying evaluation frameworks to test model outputs - Production experience with RAG and fine-tuning models - Demonstrated ability to automate large-scale API interactions and scripting for prompt testing, minimizing manual processes - Experience with LLMOps practices, including model governance, version control, performance monitoring, and lifecycle management - Strong stakeholder management skills and ability to collaborate effectively across technical and business teams - Proven track record of translating complex technical concepts into actionable business insights for diverse audiences - Analytical mindset with experience using Excel, Power BI, or Google Analytics - Solid understanding of NLP techniques - To build better prompts and leverage AI tools effectively - Excellent judgment with the ability to prioritize and independently drive projects forward while managing multiple stakeholder relationships - Experience working in agile, sprint-based development environments; familiarity with tools such as Azure Boards or Asana Our Commitment to an Inclusive Workplace We welcome people from all backgrounds who seek the opportunity to help build a future where professional services are readily available to all. If you have curiosity, passion, and a collaborative spirit, come work with us. Pearl is committed to an inclusive workplace. Pearl is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status. AI Disclosure & Informed Consent Artificial intelligence (AI) technology may be used during the hiring process to record, transcribe, analyze, and rank interview responses. By submitting your application and participating in the interview process, you acknowledge and consent to the use of AI technology in the hiring process. For more information see our AI Disclosure and Consent Policy. #LI-Remote

• Integrate LLMs and other GenAI models into web applications through efficient API design and implementation. • Build and optimize API endpoints to allow seamless, real-time interaction between front-end applications and back-end AI models. • Design and develop secure, scalable, and high-performing microservices for AI model deployment. • Develop robust back-end systems in Python to support the deployment, scalability, and maintenance of GenAI models. • Build and maintain data pipelines, including preprocessing data and post-processing AI model outputs for consumption by applications. • Use Kubernetes and Docker for containerization and orchestration to ensure scalable deployment and management of AI applications. • Implement continuous integration and continuous deployment (CI/CD) pipelines for automated testing and deployment of code changes. • Maintain a scalable and secure cloud infrastructure, leveraging platforms such as Google Cloud Platform, or Azure for model training, storage, and deployment. • Utilize vector databases (e.g., Pinecone, Weaviate, or Faiss) to manage and retrieve embeddings for efficient similarity search and recommendation systems. • Optimize and fine-tune LLMs to improve performance based on application needs.

• Architect and build full-stack, enterprise-grade platforms using reusable and modular agentic workflow patterns • Translate inputs from internal product teams into scalable, AI-powered workflows and services • Design and implement agentic workflows, including task decomposition and agent orchestration • Apply enterprise integration patterns to connect AI workflows with internal platforms and external systems • Guide and supervise coding assistants and AI agents to accelerate delivery • Design and operate event-driven architectures using AWS native services • Build secure Python back-end services for AI agents and enterprise integrations • Develop React-based front-end applications supporting complex user workflows • Build and operate multi-tenant architectures with security and compliance