AI Engineer

Job Title: AI Engineer

Location: New York, NY, Atlanta, GA, or 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 work across internal AI tooling, our internal AI platform, and AI capabilities within existing products, helping bring practical AI solutions into production across the organization.

You’ll contribute to a range of applied AI initiatives, from improving existing products and workflows to developing new AI-powered capabilities where appropriate. The scope may include prompt and context engineering, AI security, AI DevOps and hosting, evaluation frameworks, harnesses, benchmarks, and production deployment.

We’re looking for someone who is deeply technical, passionate about AI development, and eager to grow with us as we scale.

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Responsibilities**

• Develop and improve internal AI tooling, platform capabilities, and AI-enabled product functionality, including integrating AI capabilities and APIs into existing products as needed
• Build LLM-powered solutions using prompt engineering, context engineering, RAG, agentic workflows, and generative AI
• Create and maintain AI harnesses, evals, benchmarks, and testing frameworks to measure quality, reliability, and performance
• Apply ML algorithms such as linear regression, logistic regression, tree-based methods, and neural networks where applicable
• Contribute to secure, scalable AI architecture, infrastructure, DevOps, hosting, and system optimization leveraging AWS services
• Work cross-functionally with product, data engineering, and software engineering teams to align AI initiatives with business needs