Position Summary

The AI Engineer designs, develops, deploys, and supports AI-driven solutions for anesthesia and perioperative medicine. Working with anesthesiologists, clinicians, researchers, engineers, and IT professionals, this role applies large language models (LLMs), agentic AI, machine learning (ML), and advanced analytics to clinical and operational data.

The position focuses on building predictive, generative, and intelligent AI systems that enhance clinical decision-making, automate documentation, improve perioperative workflows, and support research and operational excellence. Responsibilities include model development, deployment, monitoring, governance, and integration within secure healthcare environments.

Key Responsibilities

• Develop AI solutions using LLMs, NLP, ML, retrieval-augmented generation (RAG), and agentic AI architectures.
• Design and implement predictive and generative models for anesthesia risk assessment, operating room forecasting, perioperative decision support, documentation automation, and complication prediction.
• Build AI agents that interact with clinical data sources, APIs, and knowledge systems to support clinical and operational workflows.
• Integrate and prepare data from EHRs, anesthesia systems, surgical scheduling platforms, and physiologic monitoring systems.
• Develop and maintain production AI workflows, including model training, validation, deployment, monitoring, and lifecycle management using MLOps practices.
• Implement AI governance processes, including performance monitoring, bias detection, drift management, explainability, and regulatory compliance.
• Develop APIs, data pipelines, dashboards, visualizations, and reporting solutions to support clinicians and operational leaders.
• Collaborate with interdisciplinary teams to identify opportunities for AI-driven improvements in patient outcomes, workflow efficiency, and operational performance.
• Support AI research, innovation initiatives, publications, and clinical analytics programs.

Minimum Qualifications

Education

• Master’s degree in Computer Science, Engineering, Artificial Intelligence, Biomedical Informatics, or a related field, or equivalent experience.

Experience

• 2-3 years of related experience in AI, machine learning, data science, or healthcare analytics.

Technical Skills

• Strong knowledge of machine learning, deep learning, statistical modeling, and AI solution development.
• Experience with LLMs, generative AI platforms, agentic AI systems, NLP, and RAG architectures.
• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Experience with SQL, cloud technologies (AWS, Azure, or GCP), APIs, data pipelines, and model deployment.
• Familiarity with MLOps, containerization technologies (Docker, Kubernetes), model monitoring, and lifecycle management.

Healthcare & Clinical Informatics

• Experience working with healthcare data and analytics preferred.
• Familiarity with EHR systems (e.g., Epic), healthcare data standards (FHIR, HL7), and clinical terminology systems (ICD, SNOMED, CPT).
• Understanding of perioperative workflows, anesthesia documentation, and clinical decision support is highly desirable.
• Knowledge of HIPAA-compliant environments, AI governance, model validation, bias detection, fairness, and explainability.

Collaboration & Communication

• Ability to work effectively with clinicians, researchers, engineers, and operational leaders.
• Ability to translate clinical needs into technical solutions and communicate complex findings to technical and non-technical audiences.

Preferred

• Experience designing AI agents and workflow automation solutions.
• Experience generating, evaluating, and validating AI-assisted clinical documentation and summaries