Applied AI Engineer (Medtech)

TL;DR

Applied AI Engineer (Medtech): Designing and deploying end-to-end AI solutions and agent-based pipelines for healthcare data platforms with an accent on LLM integration and scalable production systems. Focus on building AI-native capabilities to transform healthcare data exploration and internal engineering productivity.

Location: Must be based in the United States. Hybrid options available in San Francisco and New York City; otherwise, remote within the US.

Salary: $166,000 - $224,000 USD

Company

hirify.global reduces the global burden of disease using the Healthcare Map to provide a precise view of the U.S. healthcare system.

What you will do

• Ship production AI features to improve the precision and intelligence of the Komodo platform.
• Design and deploy agent-based AI pipelines and orchestration frameworks for LLM-driven workflows.
• Develop internal AI productivity tools to accelerate engineering workflows across the company.
• Prototype and validate new AI approaches using emerging research and model capabilities.
• Implement monitoring, evaluation, and observability frameworks for deployed AI services.
• Collaborate with product and data teams to define requirements and deliver scalable AI solutions.

Requirements

• Experience building production-grade AI systems or AI-powered applications.
• Strong proficiency in Python.
• Expertise in LLMs, prompt engineering, and agent-based architectures.
• Familiarity with GenAI tools such as vLLM, CrewAI, Strands, and OpenAI APIs.
• Ability to design evaluation frameworks and monitoring systems for AI features.
• Must be based in the United States.

Nice to have

• Healthcare data expertise.
• Experience with distributed computing frameworks like Spark, Snowflake, or Databricks for large-scale data processing.

Culture & Benefits

• Comprehensive health, dental, and vision insurance.
• 401(k) with company match.
• Flexible time off and holidays.
• AI-first engineering culture emphasizing active experimentation and contribution to best practices.
• Hybrid work model with hubs in San Francisco, New York City, and Chicago.