Applied AI Engineer (LLMs, Agents, and Healthcare AI)

About the role

This is not a traditional data science role. This is a hands-on engineering role focused on building, deploying, and scaling real-world AI applications that create measurable impact across clinical, operational, and member experiences.

Responsibilities

• Design, build, and deploy AI-powered applications from concept to production.
• Rapidly prototype new ideas and transform them into production-ready systems.
• Partner directly with clinicians, operators, and business stakeholders to identify high-value opportunities.
• Deliver solutions that create measurable operational, clinical, or member-facing impact.
• Design and deploy autonomous and semi-autonomous AI agents.
• Implement multi-agent workflows that automate complex healthcare processes.
• Evaluate and integrate modern agent frameworks and orchestration platforms.
• Build AI assistants that support clinical operations, member engagement, and internal productivity.
• Build applications leveraging state-of-the-art Large Language Models.
• Develop Retrieval-Augmented Generation (RAG) systems across structured and unstructured healthcare data.
• Optimize prompts, workflows, evaluation systems, and agent behavior.
• Implement knowledge retrieval systems that unlock value from clinical, genomic, imaging, and operational data.
• Build scalable data pipelines and AI services.
• Create reusable AI components, APIs, and internal platforms.
• Improve reliability, observability, performance, and security of AI systems.
• Support deployment and monitoring of production AI applications.
• Take ownership from idea through production deployment.
• Work cross-functionally with engineering, clinical, operations, and leadership teams.
• Continuously evaluate and improve AI solutions based on real-world outcomes.

Requirements

• Healthcare Experience (Required): 4+ years of experience building software, AI, machine learning, or data-driven applications within healthcare, life sciences, biotechnology, genomics, diagnostics, digital health, or clinical environments. Direct experience working with healthcare data, including one or more of: Clinical records, Laboratory data, Genomics data, Imaging reports, Physician documentation, Patient communications, Healthcare operational workflows, Strong understanding of healthcare terminology, clinical workflows, and the practical challenges of deploying AI solutions in healthcare settings.
• AI Engineering Experience (Required): Proven experience building and deploying production AI applications. Hands-on experience with Large Language Models (LLMs) and modern AI application development. Experience with Retrieval-Augmented Generation (RAG), agentic AI systems, prompt engineering, and workflow automation. Strong product mindset with the ability to identify business problems and rapidly build solutions. Experience deploying systems used by real customers, clinicians, patients, or operational teams.
• Technical Skills (Required): Strong proficiency in Python. Experience with SQL and modern database technologies. Experience with APIs, integrations, and distributed systems. Familiarity with cloud platforms and modern software engineering practices. Strong understanding of software architecture, testing, and deployment.

Qualifications

• Healthcare Experience (Required): 4+ years of experience building software, AI, machine learning, or data-driven applications within healthcare, life sciences, biotechnology, genomics, diagnostics, digital health, or clinical environments. Direct experience working with healthcare data, including one or more of: Clinical records, Laboratory data, Genomics data, Imaging reports, Physician documentation, Patient communications, Healthcare operational workflows, Strong understanding of healthcare terminology, clinical workflows, and the practical challenges of deploying AI solutions in healthcare settings.
• AI Engineering Experience (Required): Proven experience building and deploying production AI applications. Hands-on experience with Large Language Models (LLMs) and modern AI application development. Experience with Retrieval-Augmented Generation (RAG), agentic AI systems, prompt engineering, and workflow automation. Strong product mindset with the ability to identify business problems and rapidly build solutions. Experience deploying systems used by real customers, clinicians, patients, or operational teams.
• Technical Skills (Required): Strong proficiency in Python. Experience with SQL and modern database technologies. Experience with APIs, integrations, and distributed systems. Familiarity with cloud platforms and modern software engineering practices. Strong understanding of software architecture, testing, and deployment.