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Impiricus

AI Engineer

New York, NY, Atlanta, GA, or Remote, USA (Remote)$130k–$170kfull-timemidAdded today

About this role

Impiricus is seeking a hands-on AI Engineer to develop and deploy AI solutions across internal tooling, platforms, and products. You'll work on LLM-powered applications, evaluation frameworks, and scalable AI infrastructure, collaborating with cross-functional teams in a fast-growing healthcare technology company.

What you'll do

  • Develop and enhance internal AI tooling, platform capabilities, and AI-enabled product features
  • Build LLM-powered solutions using prompt engineering, RAG, agentic workflows, and generative AI
  • Create and maintain evaluation harnesses, benchmarks, and testing frameworks for AI quality and performance
  • Apply ML algorithms including regression, tree-based methods, and neural networks to solve business problems
  • Design secure, scalable AI architecture and DevOps leveraging AWS services
  • Collaborate with product, data engineering, and software teams to align AI initiatives with business goals

What they're looking for

  • Backend software development with AI/ML focus
  • Generative AI and prompt engineering
  • Machine learning algorithms and modeling
  • AWS infrastructure (EC2, S3, networking)
  • Python or similar ML-focused programming languages
  • AI evaluation frameworks and benchmarking
  • Computer networking and systems design
  • RAG and agentic workflow development

Benefits

  • Competitive base salary of $130,000–$170,000
  • Professional and personal growth opportunities
  • Employee well-being programs and support
  • Flexible work location (New York, Atlanta, or remote)
  • Opportunity to work in high-growth, Deloitte Fast 500 company
  • Mentorship and learning in cutting-edge AI space
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Impiricus

Impiricus builds an AI-powered healthcare engagement platform designed for life sciences companies. The company is hiring full-stack software engineers and QA automation engineers to develop scalable digital solutions with LLM workflows and ensure product quality through automated testing frameworks.

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Likely interview questions

  • Walk us through a recent project where you built an LLM-powered solution from prompt engineering to production—what challenges did you face?
  • How do you approach designing evaluation frameworks and benchmarks for generative AI models?
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